CN114783577A

CN114783577A - Data analytics system, method and program product for healthcare

Info

Publication number: CN114783577A
Application number: CN202210340245.3A
Authority: CN
Inventors: 恩佐·泽洛奇
Original assignee: En ZuoZeluoqi
Current assignee: En ZuoZeluoqi
Priority date: 2021-10-27
Filing date: 2022-04-01
Publication date: 2022-07-22
Also published as: CA3146318A1

Abstract

A block chain based program is provided that includes everything to transform and flow participants' personal medical records, histories, and documents in a single portal such that: appointing with medical practitioners; a flow medical diagnosis process; providing a counterbalance to counteract medication from improper medical examination, testing, overdosing; and rewarding the user with the available credit points. The participants are provided with advertising content paid for by the private-party advertisers to provide additional credit points for consumption of the advertising content. The medical records at least partially based on the conversion of the blockchain based procedure coordinate the organ donations immediately, also facilitating participant purchase of medications. Organized and/or tracked shipping and recycling procedures for pharmaceuticals are also available. Each individual health insurance claim filed by a citizen can be processed and promoted in an absolutely transparent manner.

Description

Data analytics system, method and program product for healthcare

Statement of copyright

A portion of the disclosure of this patent document contains material which is subject to copyright protection by the author of the patent document. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the patent and trademark office patent file or records, but otherwise reserves all copyright rights whatsoever.

Technical Field

The present disclosure relates to the field of healthcare, and more particularly, to a data analytics system, method and program product for processing health insurance claims and targeted advertisement-based healthcare management.

Background

One or more embodiments of the present invention are generally directed to providing a universal system to optimize the provision of healthcare-related services including health insurance, identification of appropriate physicians, and provision of related healthcare services. The efficiency of patient-to-provider communications is enhanced by the use of advanced computer science related techniques such as machine learning, artificial intelligence and blockchains, wherein the costs associated with implementation and ongoing maintenance of system operation are at least partially offset by private parties that target advertising to identified patients and/or consumers according to their respective needs.

More particularly, certain embodiments of the present invention relate to providing affordable and available healthcare to low-income and medium-income consumers, and implementing a system that allows participants to quickly and conveniently process their respective healthcare-related bills. Some embodiments may provide means for processing and promoting health insurance claims. Participants may access the different healthcare-related subsystems and/or platforms through a single central database that also allows for the confidential sharing of health-related information and records with physicians, other healthcare providers, and healthcare institutions (e.g., hospitals) worldwide. The disclosed system and method of use thereof further provide for addressing patient and/or consumer related logistical needs, such as ordering physicians, switching between various healthcare related policies, recycling of unused medications, and obtaining optimal pricing for physicians, medications, hospitals, etc.

The following background information may present examples of certain aspects of the prior art (e.g., without limitation, methods, facts, or common sense) that, while desirable to assist the reader in further educating the reader about additional aspects of the prior art, should not be construed as limiting the present invention or any embodiments thereof to anything stated or implied therein or inferred thereby. Systems and methods of using the same may be known with respect to implementing medical assessment (particularly machine learning) workflows and procedures. Additionally, computer-implemented methods, systems, and computer-readable storage media may have been provided for use with clinical support systems for identifying and providing information regarding causal relationships associations between individual patient attributes and one or more adverse events. Systems, methods and devices for personal medical care, intelligent analysis and diagnosis are known, as are systems and methods for developing comprehensive health profiles.

In view of the above, it is clear that these conventional techniques are not perfect and leave room for a more optimal approach.

Disclosure of Invention

To address, at least in part, the above technical problems, embodiments of the present disclosure provide a data analytics system, method, and program product for processing health insurance claims and targeted advertisement-based healthcare management.

The technical solution of the present disclosure refers to the specific embodiments described below.

Drawings

The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:

FIG. 1 illustrates an exemplary schematic diagram of a system of virtual intelligent healthcare-related services systems;

FIG. 2 illustrates an exemplary schematic diagram of a system of virtual intelligent healthcare-related services systems;

FIG. 3 illustrates an exemplary flow diagram of an integrated healthcare-related services system for virtual assistance and wearable technology;

FIG. 4 illustrates an exemplary schematic diagram of a system of virtual intelligent healthcare-related services systems;

fig. 5 illustrates an example "cloud" based system of virtual intelligent healthcare-related services systems;

FIG. 6 illustrates a notification system of an example of a virtual intelligent healthcare-related services system;

FIG. 7 illustrates an organ tracking and notification system of an example of a virtual intelligent healthcare-related services system;

FIG. 8 illustrates an example "cloud" based system of virtual intelligent healthcare-related services systems;

FIG. 9 illustrates an encryption system of an example of a virtual intelligent healthcare-related services system;

FIG. 10 illustrates an exemplary schematic diagram of a "cloud" based system of virtual intelligent healthcare-related services systems;

FIG. 11 illustrates an example "cloud" based system of virtual intelligent healthcare-related services systems;

FIG. 12 illustrates an example system that integrates wearable technology and robotics into a virtual intelligent healthcare-related services system;

FIG. 13 illustrates an example system that integrates wearable technology and robotics into a virtual intelligent healthcare-related services system;

fig. 14 illustrates an example "cloud" based system of virtual intelligent healthcare-related services systems implementing machine learning and microservices;

fig. 15 illustrates an example "cloud" based system of virtual intelligent healthcare-related services systems;

FIG. 16 illustrates an example "cloud" based system of virtual intelligent healthcare-related services systems;

FIG. 17 illustrates an example notification system for fraud prevention for a virtual intelligent healthcare-related services system;

FIG. 18 illustrates a block diagram showing an exemplary client/server system that may be used by exemplary web/network-enabled embodiments of the present invention;

FIG. 19 illustrates a block diagram showing a conventional client/server communication system that may be used by exemplary network/networking-enabled embodiments of the present invention;

FIG. 20 illustrates a flow diagram of an exemplary method for tracking, analyzing, storing and facilitating personal medical records, histories and documentation using blockchain techniques according to an embodiment of the present invention;

FIG. 21 illustrates a flow diagram of an exemplary method of a sub-routine of an embodiment for tracking, analyzing, storing and facilitating personal medical records, histories and documents using blockchain techniques according to an embodiment of the invention;

FIG. 22 illustrates a flow diagram of an exemplary method of sub-routine of an embodiment for tracking, analyzing, storing and facilitating personal medical records, histories and documentation using blockchain techniques according to an embodiment of the invention;

FIG. 23 illustrates an expanded flow diagram of an additional embodiment of an exemplary method for predicting what will occur therein based on symptoms and individual genetic features by using machine learning to make medical diagnosis more accurate and available in accordance with an embodiment of the present invention;

FIG. 24 illustrates an expanded flow diagram of an additional embodiment of an exemplary method for predicting what will occur therein based on symptoms and individual genetic features by using machine learning to make medical diagnosis more accurate and available in accordance with an embodiment of the present invention;

FIG. 25 illustrates an exemplary embodiment of an integrated graphical user interface;

FIG. 26 illustrates an exemplary embodiment of an integrated graphical user interface;

FIG. 27 illustrates an exemplary embodiment of an integrated graphical user interface; and

FIG. 28 illustrates an exemplary embodiment of an integrated graphical user interface.

The drawings in the drawings are not to scale unless otherwise indicated.

Detailed Description

The invention is best understood by reference to the detailed drawings and description set forth herein.

Embodiments of the invention are discussed below with reference to the figures. However, those skilled in the art will readily appreciate that the detailed description given herein with respect to these figures is for explanatory purposes as the invention extends beyond these limited embodiments. For example, it should be understood that one skilled in the art, given the teachings of the present invention, will recognize numerous alternative and suitable ways to implement the functions of any given detail described herein, beyond the specific implementation choices in the embodiments described and illustrated below, depending on the needs of a particular application. That is, the modifications and variations of the present invention are too numerous to list, but they are within the scope of the present invention. Furthermore, where appropriate, singular words are to be understood as being plural and vice versa; positive words are understood as negative and vice versa; also, alternative embodiments do not necessarily imply that the two are mutually exclusive.

It is also to be understood that this invention is not limited to the particular methodology, compounds, materials, manufacturing techniques, uses, and applications described herein, as these may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention. It must be noted that, as used herein and in the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "an element" is a reference to one or more elements and includes equivalents thereof known to those skilled in the art. Similarly, for another example, a reference to a "step" or "means" is a reference to one or more steps or means, and may include sub-steps and dependent means. All words used should be understood in the most inclusive sense possible. Thus, the term "or" should be understood to have the definition of a logical "or" rather than the definition of a logical "exclusive or" unless the context clearly requires otherwise. Structures described herein are also to be understood as referring to functional equivalents of such structures. Unless the context clearly dictates otherwise, it should also be understood that such may be interpreted as representing approximate language.

All approximating language, as used herein throughout the disclosure and claims, should be construed as meaning "approximately" rather than "perfectly," and thus may be applied as a meaningful modifier to any other term, specified parameter, quantity, quality, or concept. Approximating language includes, but is not limited to, terms such as "substantially," "approximately," "nearly," "approximately," "about," "approximately," "most," "essentially," "very approximately," and the like.

As will be established in greater detail below, it has been expressly stated as early as 1939 that approximating words in the claims are not indefinite, even when such limitations are not defined or indicated in the specification.

See, for example, Ex part Mallory,52USPQ 297,297(pat. off. bd. app.1941), wherein the court states that "the examiner has deemed most claims to be inaccurate because it is clear that the laminar film will not be completely removed. The claims indicate that the film is "substantially" removed and that, for the intended purpose, it is believed that a negligible fraction of the film may remain. We therefore consider the claims to be sufficiently accurate ".

It is noted that the claims need only "reasonably apprise those skilled in the art" as to their scope to meet the explicit requirements. See Energy Absorption sys, inc. v. road Safety services, inc. v. app.96-1264, slip op. at 10(fed. cir. july 3,1997) (not disclosed) hybrid v. monoclonal Antibodies, inc. 802f.2d1367,1385,231uspq 81,94(fed. cir.1986), cert. derived, 480 u.s.s.947 (1987). Furthermore, the use of modifiers in the claims, such as "substantially" and "essentially", by themselves, does not obscure the claims. See Seattle Box Co.v. Industrial cladding, Inc.,731F.2d 818,828-29,221USPQ 568,575-76(Fed. cir. 1984).

Further, the ordinary and customary meaning of a term such as "substantially" includes "reasonably close to: near, nearly, about, meaning approximate terms. See for Frye, Appeal No.2009-006013,94USPQ2d 1072,1077,2010WL 889747 (b.p.a.i.2010). The term "substantially" may denote, depending on its usage, either an approximate language or a magnitude language. De ering Precision Instruments, l.l.c.v.vector Distribution sys., inc.,347f.3d 1314,1323(fed. cir.2003) (the double ordinary meaning of the term "substantially" is considered to mean approximate or magnitude terms). Here, when referring to the "substantially half" limitation, the specification uses the word "about" in place of the word "substantially" (fact 4). (fact 4). The ordinary meaning of "substantially half" is thus reasonably close or near to the midpoint between the forwardmost point of the upper or outsole and the rearwardmost point of the upper or outsole.

Similarly, the term "substantially" is recognized in case law as having the dual ordinary meaning of representing either an approximate term or a magnitude term. See Dana corp.v. american Axle & Manufacturing, inc., civ.app.04-1116,2004u.s.app.lex 18265, 13-14(fed.cir. august 27,2004) (not disclosed). The term "substantially" is commonly used by the drafter of the claims to refer to approximations. See Cordis corp.v. medtronic AVE inc.,339f.3d 1352,1360(fed. cir.2003) ("the patent does not set any numerical criteria to determine if the thickness of the wall is ' substantially uniform". the term ' substantially ' as used herein means approximately. See also the assembly Precision Instruments, LLC v.vector Distribution sys, inc.,347f.3d 1314,1322(fed. cir.2003); epcon Gas sys., inc.v. bauer Compressors, inc.,279f.3d1022,1031 (fed. cir.2002). We have found that in the claims referring to the patent, the term "substantially" is used in the sense that: by "substantially uniform wall thickness" is meant having an approximately uniform wall thickness.

It should also be noted that such approximating words, as previously conceived, expressly limit the scope of the claims, e.g. "substantially parallel", such that the adverb "substantially" does not extend the parallel meaning. It is therefore well established that such approximating words, as previously conceived (e.g. like the phrase "substantially parallel") contemplate some degree of deviation from perfect (e.g. not perfectly parallel), and that such approximating words, as previously conceived, are descriptive terms commonly used in the patent claims to avoid strict numerical boundaries for the specified parameters. If the ordinary language of a claim that relies on such approximating words as contemplated above is clear and does not contradict any written description herein or in its drawings, it is not appropriate to rely on this written description, drawings, or prosecution history to add limitations to any claim of the invention with respect to such approximating words as contemplated above. That is, in such cases, it is not permissible to rely on written descriptions and prosecution history to reject the ordinary and customary meaning of the word itself. See, for example, Liquid Dynamics corp.v. vaughan co.,355f.3d 1361,69USPQ2d 1595,1600-01(fed. cir.2004). The common language of phrase 2 requires "substantially helical flow". The term "substantially" is a meaningful modifier, meaning "approximately" rather than "perfectly". In Cordis corp.v. medtronic AVE, inc.,339f.3d 1352,1361(fed. cir.2003), the local court imposes a precise numerical limit on the term "substantially uniform thickness". We note that a proper interpretation of this term is "having a thickness that is largely or nearly uniform," unless something in the prosecution history imposes a "clear and unmistakable disclaimer," which is to be narrowed to such a simple language interpretation. Id. in Anchor Wall Systems v. rockwood Retaining Walls, inc.,340f.3d 1298,1311(fed.cir.2003) "id.at 1311. Similarly, the plain language of claim 1 requires neither perfect helical flow nor flow that returns to the center exactly after one revolution (this restriction only occurs as a logical result of requiring perfect helical flow).

The reader should understand that case law generally admits that the double ordinary meaning of such approximating language, as previously conceived, is intended to mean approximating terms or magnitude terms; see, for example, the department of law for interpretation of the meaning of the word "substantially" in the patent claims, l.l.c.v.vector distribution. sys., inc.,347f.3d 1314,68USPQ2d 1716,1721(fed. cir.2003), cert.derived, 124s.ct.1426 (2004). See also Epcon,279f.3d at 1031 ("phrase 'substantially constant' denotes approximate language and phrase 'substantially lower than' denotes magnitude language, i.e. not insubstantial"). Further, see, e.g., Epcon Gas sys., inc.v. bauer Compressors, inc.279 f.3d1022(fed. cir.2002) (the terms "substantially constant" and "substantially below"); zodiac Pool Care, Inc. v. Hoffinger Indus, Inc.,206F.3d 1408(Fed. Cir.2000) (the interpretive term "substantially inward"); york prods, inc.v. cent. trap Farm & Family ct, 99f.3d 1568(fed. cir.1996) (the interpretive term "substantially its entire height"); instruments inc.v. cypress Semiconductor corp.,90f.3d 1558(fed.cir.1996) (the term "substantially in the public plane" is interpreted). In conducting their analyses, court instructions begin with the ordinary meaning of claim terms to those of ordinary skill in the art. Prima Tek,318F.3d at 1148. Reference to a dictionary and our case indicates that the term "substantially" has many ordinary meanings. As with the local court of law, "substantially" may mean "significantly" or "substantially large. The term "substantially" may also mean "largely" or "essentially". Webster new dictionary of the 20 th century 1817 (1983).

Approximating language, as previously conceived, may also be used in phrases establishing approximating ranges or limitations, wherein the endpoints are inclusive and approximate, rather than perfect; see, for example, AK Steel corp.v. sollac,344f.3d 1234,68USPQ2d 1280,1285(fed. cir.2003), where the court says we conclude that the phrase "up to about 10%" includes "about 10%" endpoints. As indicated by AK Steel, when the object of the preposition "up" is non-numeric, the most natural meaning is to exclude the object (e.g., paint a wall to a door). On the other hand, when the subject is a numerical limit, as indicated by Sollac, the normal meaning is to include the numerical upper limit (e.g., several to ten, up to seven passengers). Because we have numerical limitations- "about 10%" -the ordinary meaning is inclusive of the endpoints.

In the present description and claims, the use of such approximating words as herein before conceived is intended to avoid strict numerical boundaries for the specified parameters of the modification, as recognized by Pall corp.v. micron separators, inc.,66f.3d 1211,1217,36USPQ2d 1225,1229(fed. cir.1995), wherein it is stated that the term "well known," when used reasonably to describe the subject matter such that its scope will be understood by those skilled in the art, and to distinguish the claimed subject matter from the prior art, is not uncertain ". See also, Verve LLC v.crane Cams inc.,311f.3d 1116,65 usppq 2d 1051,1054(fed. cir.2002). When the nature of the invention is warranted, expressions such as "substantially" are used in the patent document to accommodate minor variations that may be suitable for protecting the invention. Such usage is likely to satisfy the guidelines of the "specifically pointing out and distinctly claiming" the present invention, 35 u.s.c. § 112, and may indeed be necessary to provide the inventors with the benefit of their invention. In Andrew corp.v. gabriel elecs.inc.,847f.2d 819,821-22, 6USPQ2d 2010,2013(fed. cir.1988), the use of "substantially equal" and "very similar" can be used to accurately describe the invention in terms of being technically sound and not encompassing the prior art. The court re-explains in Ecolab inc.v. envirochem, inc.,264f.3d 1358,1367,60USPQ2d 1173,1179(fed. cir.2001), that the term ' substantially ' is a descriptive term commonly used in the patent claims, as the term ' about ', to ' avoid specifying strict numerical boundaries for parameters, see Ecolab inc.v. envirochem inc.,264f.3d 1358,60USPQ2d 1173,1179(fed. cir.352001), where the court found that the use of the term "substantially" to modify the term "unity" did not render the phrase so ambiguous as to not determine the scope of the claims.

Similarly, other courts have noted that, like the term "about," the term "substantially" is a descriptive term commonly used in patent claims to "avoid strict numerical boundaries for specified parameters. See, for example, Pall corp.v. micron seps, 66f.3d 1211,1217,36USPQ2d 1225,1229(fed. cir.1995); see, for example, Andrew corp.v. gabriel elecs.inc.,847f.2d 819,821-22, 6USPQ2d 2010,2013(fed. cir.1988) (note that terms such as "approximate to each other," "near," "substantially equal," and "very similar" are commonly used in the patent claims, and that such usage has been accepted and supported by the court of patent prosecution when reasonably describing the claimed subject matter to one skilled in the art of the present invention and distinguishing it from the prior art). In this case, "substantially" avoids strict 100% non-uniformity boundaries.

Indeed, the foregoing recognition of such approximating words as previously conceived has been established as early as 1939, see Ex part Mallory,52USPQ 297,297(pat. We therefore consider the claims to be sufficiently accurate ". Similarly, in Hutchison,104f.2d 829,42USPQ 90,93(c.c.p.a.1939), the court of law indicates "realizing that 'the basic distance' is a relative and somewhat uncertain term or phrase, but that terms and phrases of this nature are not uncommon in patents where their meaning can be reasonably clearly determined according to the technology involved".

Applicant thus proposes that, at least for the reasons stated above, any claim of this patent that uses any approximating word shall not be deemed appropriate by any examiner as an admission that such claim is inconclusive.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Preferred methods, techniques, devices, and materials are described, although any methods, techniques, devices, or materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention. Structures described herein are also to be understood as meaning functional equivalents of the recited structures. The invention will be described in detail below with reference to embodiments of the invention shown in the drawings.

References in the preamble of the claims to "apparatus", "device", "system", etc. should be interpreted broadly as "any structure that meets the claim terminology, exempts from any specific structure/type that has been specifically denied or excluded, or acknowledges/implies any specific structure/type that is prior art in this specification or that does not fulfill the purpose/aspect/object of the invention. Furthermore, to the extent that this specification discloses objects, aspects, functions, objectives, results or advantages of the present invention in which specific prior art structures and/or method steps are capable of being performed in a very different manner, the disclosure of the present invention is intended to, and should also implicitly, include and cover additional corresponding alternative embodiments which are identical to the explicitly disclosed embodiments in other respects, except that they exclude the described prior art structures/steps, and which accordingly should be considered as providing sufficient disclosure to support the corresponding negative limitations in the claims which claim such alternative embodiments, excluding such very different prior art structures/steps.

From reading the present disclosure, other variations and modifications will be apparent to persons skilled in the art. Such variations and modifications may involve equivalent and other features which are already known in the art, and which may be used instead of or in addition to features already described herein.

Although claims have been formulated in this application to particular combinations of features, it should be understood that the scope of the disclosure of the present invention also includes any novel feature or any novel combination of features disclosed herein either explicitly or implicitly or any generalisation thereof, whether or not it relates to the same invention as presently claimed in any claim and whether or not it mitigates any or all of the same technical problems as does the present invention.

Features which are described in the context of separate embodiments may also be provided in combination in a single embodiment. Conversely, various features that are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable subcombination. The applicants hereby give notice that new claims may be formulated to such features and/or combinations of such features during the prosecution of the present application or of any further application derived therefrom.

Definition of

References to "one embodiment," "an embodiment," "example embodiment," "various embodiments," "some embodiments," "an embodiment of the invention," etc., may indicate that the embodiment so described may include a particular feature, structure, or characteristic, but not every possible embodiment of the invention necessarily includes the particular feature, structure, or characteristic. Further, repeated use of the phrases "in one embodiment" or "in an exemplary embodiment" or "an embodiment" does not necessarily refer to the same embodiment, although they may. Moreover, any use of phrases such as "an embodiment" in connection with "the present invention" does not in any way imply that all embodiments of the invention must include the particular feature, structure, or characteristic, but rather "at least some embodiments of the invention" include the particular feature, structure, or characteristic recited.

References to a "user" or any similar term as used herein may refer to a human or non-human user thereof. Also, unless expressly specified otherwise, "user" or any similar term as used herein is contemplated as a user at any stage of the use process, including but not limited to direct users, intermediate users, indirect users, and end users. The meaning of "user" or any similar term as used herein should not be inferred or induced in other ways by any mode of the prior art that may (or may not) provide descriptions, embodiments, examples or references in this patent.

References to "end user" or any similar term as used herein generally mean a later stage user, not an earlier stage user. Thus, it is contemplated that there may be a variety of different types of "end users" near the final stage of the use process. Where applicable, particularly with respect to the distribution channels of embodiments of the present invention, including retail products/services that are consumed by them (rather than sellers/suppliers or original equipment manufacturers), examples of "end users" may include, but are not limited to, "consumers," "buyers," "customers," "buyers," "shoppers," "enjoyers," "viewers," or personal or non-human things that in any way directly or indirectly benefit from the use or interaction of certain aspects of the present invention.

In some cases, some embodiments of the invention may provide beneficial use for more than one stage or type of use in the foregoing use process. Where such descriptions refer to multiple embodiments for various stages of a usage process, references to "end user" or any similar terminology as used herein are generally intended to exclude the farthest user from which the last of the embodiments of the invention was removed during the preceding usage.

Where applicable, particularly with respect to retail distribution channels of embodiments of the present invention, intermediary users may include, but are not limited to, any personal or non-human thing that directly or indirectly benefits in any manner from the use or interaction of some aspect of the present invention with respect to sales, original equipment manufacturing, marketing, distribution, service provision, and the like.

References to "human," "person," "human," "party," "animal," "biological," or any similar term as used herein, even if the context or particular embodiment implies a living user, manufacturer, or participant, it is to be understood that such features are by way of example only and not limitation, as it is contemplated that any such use, manufacture, or participation of a biological entity associated with making, using, and/or participating in an embodiment of the invention in any way may be replaced by an analog implemented by a suitably configured non-biological entity, including but not limited to automated machines, robots, humanoids, computing systems, information handling systems, artificial intelligence systems, and the like. It is further contemplated that those skilled in the art will readily recognize the fact that such animate manufacturers, users, and/or participants of embodiments of the present invention may be replaced, in whole or in part, by such inanimate manufacturers, users, and/or participants of embodiments of the present invention.

As such, when those skilled in the art recognize the fact that such animate manufacturers, users, and/or participants of embodiments of the present invention may be replaced, in whole or in part, by such inanimate manufacturers, users, and/or participants of embodiments of the present invention, it will be readily apparent, in light of the teachings of the present invention, how to adjust the described embodiments to suit such inanimate manufacturers, users, and/or participants of embodiments of the present invention. Therefore, the invention is to cover all such modifications, equivalents, and alternatives falling within the spirit and scope of such adaptations and modifications, at least in part, as such inanimate entities.

Reference to "healthcare" or "health care" means maintaining or improving health by preventing, diagnosing, and treating diseases, ailments, injuries, and other physical and mental injuries in a person. Healthcare is given by healthcare professionals in the healthcare field of the league. Physicians and physician assistants are part of these medical professionals. Dental, obstetrical, nursing, medical, optometric, audiological, pharmaceutical, psychological, occupational, physical, and other health professionals are all part of healthcare. It includes work done in providing primary, secondary and tertiary care as well as public health.

The opportunities to obtain healthcare may vary from country to country, community to community, and individual to a large extent, subject to social and economic conditions, as well as to health policies. Providing healthcare services means "using personal healthcare services in a timely manner to obtain the best possible health outcome". [ origin: acquisition of U.S. healthcare services. national academy of sciences publishers, national academy of sciences, engineering and medicine, 1993 ]. Factors to be considered in obtaining healthcare include financial limitations (e.g., insurance coverage), geographic impediments (e.g., additional traffic costs to use such services, the possibility of paid vacation), and personal limitations (lack of ability to communicate with healthcare providers, poor health literacy, low income). [ origin: introduction of medical care acquisition in rural communities 2019, retrieved in 2019, 14.06 months. Limitations on healthcare services negatively impact the use of healthcare services, the effectiveness of treatments, and the overall outcome (happiness, mortality).

Healthcare systems are an organization established to meet the health needs of a target population. According to the World Health Organization (WHO), a well-functioning health care system requires financing mechanisms, reliable information upon which highly trained and well-paid workforce, decisions and policies are based, and maintenance of good health facilities to provide high quality medicine and technology. [ origin: "health topic: health system ". www.who.int world health organization. retrieve 24.11.2013 ].

An effective healthcare system can make a significant contribution to the economy, development and industrialization of a country. Healthcare has traditionally been recognized as an important determinant to promote overall physical and mental health and well-being of people around the world. An example of this is the worldwide eradication of smallpox in 1980, which was announced by the WHO as the first disease historically to be completely eliminated by conscious healthcare intervention in humans. [ origin: smallpox eradicates anniversary. geneva, 6-month-18 2010 ].

Reference to the "healthcare industry" means the convergence and integration of departments within the economic system that provide goods and services to treat patients with therapeutic, prophylactic, rehabilitative, and palliative treatments. It includes the production and commercialization of goods and services that help maintain and rebuild health. [ origin: "10 Jahre national branchkenkonferz Gesundehitswirtschaft-

Ergebnisse p.4 "(PDF). BioCon Valley GmbH. search 8/21/2015]. The modern healthcare industry is divided into many sectors and relies on cross-disciplinary teams of trained professionals and assisted professionals to meet the health needs of individuals and populations. [ origin: https:// cns. utexas. edu/health-services; and (3) retrieval date: 07-07-19; "Health Care Initiatives, Employment&Training Administration (ETA) -U.S. department of Labor "; doleta. gov. search in 2015, 2 months and 17 days]。

Reference to "health economics" means the branch of economics that relates to issues related to efficiency, effectiveness, value and behavior in the production and consumption of health and healthcare. In a broad sense, health economists study the operation of healthcare systems and health-affecting activities such as smoking.

Reference to the "health maintenance organization (" HMO ")" means a medical insurance group that provides health services at a fixed annual fee. [ origin: "BBC News-G-I-Health Maintenance Organization/HMO". News.bbc.co.uk. was retrieved in 2018, 22/3). It is an organization that provides or schedules managed care for medical insurance, self-service healthcare welfare plans, individuals and other entities on a prepaid basis, acting as a contact with healthcare providers (hospitals, doctors, etc.). The health maintenance organization act of 1973 requires that employers with 25 or more employees must provide a federally certified HMO option if they offer traditional healthcare options. [ origin: joseph L.Dorsey, "The Health Maintenance Organization Act of 1973(P.L.93-222) and Prepaid Group Practice Plan," Medical Care, Vol.13, No.1, (Jan.,1975), pp.1-9 ]. Unlike traditional loss compensation insurance, HMOs encompass the care provided by doctors and other professionals who have treated patients with guidelines and restrictions on HMOs by contractual agreement in exchange for a steady flow of patrons. HMOs encompass emergency care regardless of the status of the contract of the healthcare provider.

Reference to "medical imaging" means a technique and process that creates a visual presentation of the inside of the body, as well as the function of some organs or tissues (physiology), for clinical analysis and medical intervention. Medical imaging attempts to reveal internal structures hidden by skin and bone, and to diagnose and treat disease. Medical imaging also builds a database of normal anatomy and physiology to identify abnormalities. Although excised organs and tissues may be imaged for medical reasons, such procedures are generally considered to be part of the pathology rather than medical imaging. As a discipline, and in its broadest sense, it is part of biological imaging, combined with radiology using radiography, magnetic resonance imaging, medical ultrasonography or ultrasound, endoscopy, elastography, tactile imaging, thermography, medical photography, and nuclear medicine functional imaging techniques (positron emission tomography (PET) and Single Photon Emission Computed Tomography (SPECT)). The measurement and recording techniques used to generate the images are not primarily designed to generate images such as electroencephalograms (EEG), Magnetoencephalograms (MEG), Electrocardiograms (ECG), and others, which represent other techniques that generate data that can be readily presented as a parametric map vs. time or map containing data about the location of the measurement. In limited comparisons, these techniques can be considered as a form of medical imaging in another discipline.

Reference to "disease" means a particular abnormal condition that negatively affects part or all of the structure or function of an organism and is not due to any external injury. [ origin: "disease" in the dowish medical dictionary; white, Tim (12/19/2014), "What is the Difference Between an 'Injury' and 'Disease' for Commonwealth Injury classes? ", Tindall Gask Bentley. assembled from the original on 27October 2017, retrieved from 11-06-17 ]. A disease is generally interpreted as a medical condition associated with specific symptoms and signs. [ origin: "disease" in the Doolan medical dictionary. The disease may be caused by external factors (e.g., pathogens) or internal dysfunctions. For example, internal dysfunction of the immune system can produce a variety of different diseases, including various forms of immunodeficiency, hypersensitivity, allergy, and autoimmune disorders. In humans, illness is generally used more broadly to refer to any condition that causes pain, dysfunction, pain, social problems, or death of the afflicted person, or causes similar problems to a person in contact with the person. In this broader sense it sometimes includes injuries, disabilities, disorders, syndromes, infections, isolated symptoms, abnormal behavior, and atypical changes in structure and function, while in other contexts and for other purposes these may be considered distinguishable categories. Diseases can affect a person not only physically, but also mentally, as infections and suffering from diseases can change the affected person's opinion of life. Death from disease is known as natural cause death. There are four main types of disease: infectious diseases, defective diseases, genetic diseases (including genetic and nongenetic diseases) and physiological diseases. Diseases can also be classified in other ways, such as infectious and non-infectious diseases. The most fatal diseases in humans are coronary artery disease (blood flow blockage), followed by cerebrovascular disease and lower respiratory tract infections. [ "what is the most fatal disease in the world? ". WHO; 16May 2012; assembled from the original on 17 Decumber 2014; retrieved 12-07-14 ] in developed countries, the diseases that generally cause the most morbidity are neuropsychiatric diseases, such as depression and anxiety.

Reference to "preventive care" means measures taken for disease prevention. [ origin: hugh R.Leavell and E.Gurney Clark as "the science and art of predicting disease, predicting life, and predicting physical and mental health and efficacy Leavell, H.R., & Clark, E.G. (1979) predicting Medicine for the vector in his society (3rd ed.). Huntington, NY: Robert E.Krieger Publishing Company ]. Just as health includes a variety of physical and mental states, so are diseases and disabilities, which are influenced by environmental factors, genetic predisposition, disease factors and lifestyle choices. Health, disease and disability are dynamic processes that begin before an individual becomes aware of their own effects. Disease prevention relies on prior action and can be classified as original, [ source: "New entries" secure a filing well-bearing for the offset of the present by reclaiming to be in the views of social stress documents private ". Primal preservation source: primary, secondary and tertiary prevention, in Primal Health Research Database, on { { cite web | url ═ https:// web. area. org/web/20180815043657/http:// Primal Health area. com/gloss. php ]. [ origin: hugh R.Leavell and E.Gurney Clark as "the science and art of predicting disease, predicting life, and predicting physical and mental health and efficacy Leavell, H.R. & Clark, E.G. (1979). Prevementive Medicine for the vector in his immunity (3rd ed.). Huntington, N.Y.: Robert E.Kreiger Publishing Company ].

Reference to "artificial intelligence" means the intelligence of a machine presentation, in contrast to the natural intelligence exhibited by humans. Colloquially, the term "artificial intelligence" is commonly used to describe machines (or computers) that mimic the "cognitive" functions of humans in connection with human thinking, such as "learning" and "problem solving. [ origin: russell, Stuart j.; norvig, Peter (2009). Artificial Intelligence: A model Approach (3rd ed.). Upper Saddle River, New Jersey: Prentice Hall ]. As machines become more and more capable, tasks that are deemed to require "intelligence" are often removed from the definition of AI, a phenomenon known as AI effects. [ origin: McCorduck, Pamela (2004), Machines Who Think (2nd ed.), Natick, MA: A.K. Peters, Ltd.). One sentence in tesler's theorem says: "Artificial intelligence is something that has not been done" [ Source: malonof, mark, "Artificial significance: An significance, p.37" (PDF) ]. For example, optical character recognition has become a conventional technique that is often excluded from what is considered AI. [ origin: schank, Roger c. (1991). "Where's the AI". AI megazine. vol.12no.4.p.38 ]. Modern machine capabilities, generally classified as AI, include successful understanding of human speech [ source: russell, Stuart j.; norvig, Peter (2009). Artificial Intelligent research: AModern Approach (3rd ed.). Upper Saddle River, New Jersey: Prentice Hall. ], competition at the highest level in strategic gaming systems (such as chess and go) [ sources: https:// depemind.com/research/alphago/; and (3) retrieval date: 07-07-19], autonomous driving automobiles, intelligent routing in content distribution networks, and military simulations. Artificial intelligence can be divided into three different types of systems: analytic type, human initiation type and humanized artificial intelligence. [ origin: kaplan Andrea; michael Haenlein (2018) Siri, Siri in my Hand, who's the Fairest in the Landon the intermediates, illuminants and impedances of scientific insignia, Business Horizons,62(1) ]. Analytical AI has only features consistent with cognitive intelligence; cognitive characterizations of the world are generated and future decisions are informed using learning based on past experience. Human initiation AI has elements of cognitive and emotional intelligence; in addition to cognitive elements, human emotions are understood and considered in their decision making. Humanized AI is characterized by all types of skills (i.e., cognition, emotion, and social intelligence), can be self-conscious, and can be self-conscious in interaction with others.

Reference to "machine learning" means scientific research into algorithms and statistical models used by computer systems to efficiently perform specific tasks without the use of explicit instructions, but rather relying on patterns and reasoning. It is considered a subset of artificial intelligence. Machine learning algorithms build mathematical models based on sample data (referred to as "training data") in order to make predictions or decisions without explicitly programming execution tasks. [ origin: the definition of "not explicitly programmed" is often attributed to Arthur Samuel who created the term "machine learning" in 1959, but the phrase was not found verbatim in this publication, possibly a paraphrase that appeared later. Conference "partner engineering of Samuel (1959), the query is How do How to design solutions with out beams? "in Koza, John r.; bennett, Forrest h.; andre, David; keane, Martin A. (1996), Automated Design of the Topology and Sizing of Analog Electrical Circuits Using Genetic engineering in Design'96.Springer, Dordright pp.151-170; bishop, C.M, (2006), Pattern Recognition and Machine Learning, Springer ]. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is not feasible to develop algorithms of specific instructions to perform tasks. Machine learning is closely related to computational statistics, which focus on using computers for prediction. The study of mathematical optimization provides the fields of methodology, theory and application for the field of machine learning. Data mining is a research area in machine learning and focuses on exploratory data analysis through unsupervised learning. [ origin: bishop, C.M, (2006), Pattern Recognition and Machine Learning, Springer (stating that Machine Learning and Pattern Recognition can be viewed as two aspects of the same domain) ] [ sources: friedman, Jerome H. (1998). "Data Mining and Statistics: What's the connection? "; computing Science and statistics.29(1): 3-9 ]. In its application across business problems, machine learning is also referred to as predictive analysis.

Reference to a "blockchain" means a growing list of records linked using cryptography, called a chunk. [ origin: "Blockchains" The great chains of The bearing about The ways ". The Economist.31October 2015.Archived from The original on3July 2016. The technique behind" Bingjins "retrieved from 2016 (6/18/6) allows one who does not know or trust each other to build a reliable book. This has the meaning of far beyond cryptocurrency "; narayana, Arvind; bonneau, Joseph; felten, Edward; miller, Andrew; goldfeder, Steven (2016), Bitcoin and cryptocurrenttechnologies, a comprehensive introduction, Princeton University Press. Each chunk contains the cryptographic hash of the previous chunk [ source: narayanan, Arvind; bonneau, Joseph; felten, Edward; miller, Andrew; goldfeder, Steven (2016. Bitcoin and cryptocurrence technologies: electroconductive overview. Princeton: Princeton University Press ], timestamp, and transaction data (commonly expressed as Merckle Tree). The blockchain may be resistant to modification of the data, depending on the design. It is an "open distributed book that can efficiently and consistently record transactions between two parties". [ origin: iansitii, Marco; lakhani, Karim R. (January 2017.) "true about blockchain Harvard Business review, Harvard university, acquired from the original on 18January 2017.Retrieved 17January 2017." as a core technology for bitcoin and other virtual currencies, blockchain is an open distributed book that can efficiently and persistently record transactions between two parties "]. Used as a distributed book, blockchains are typically managed by peer-to-peer networks (peer-to-peer networks), collectively adhering to inter-node communication protocols and validating new blocks. Once recorded, the data in any given block cannot be changed retrospectively without changing all subsequent blocks, requiring consensus by most people of the network. Although blockchain records are not immutable, blockchains may be considered secure in design and embody a distributed computing system with high byzantine fault tolerance. Thus, the blockchain claims decentralized consensus. [ origin: raval, Siraj (2016), "white Is a Decentralized Application? ". Decentralized Applications, Harnessing Bitcoi's Blockchain technology, O' Reilly Media, Inc. pp.1-2. ISBN 978-1-4919-.

Reference to "Medicare" means the national health insurance program in the united states, which was initiated in 1966 at the initiation of the Social Security Administration (SSA) and is now managed by the Medicare and Medicare service Center (CMS). It provides health insurance for americans 65 years and older, young people with certain disability status as determined by the social security administration, and people with end stage renal disease and amyotrophic lateral sclerosis (ALS or lugal raynaud's disease). In 2018, Medicare provided health insurance for over 5990 million individuals — over 5200 ten thousand people aged 65 and older and about 800 million young people. [ origin: 2019an Annual Report of the medical railes (for the year 2018), April 22,2019 ]. On average, Medicare covers about half of healthcare costs for participants. Medicare finances by payroll taxes, beneficiary premiums and additional taxes from beneficiaries, copay amounts and indemnity amounts, and conventional U.S. national treasury revenues.

Reference to a "data management platform (" DMP ")" means a technical platform for collecting and managing data, primarily for digital marketing purposes. [ origin: what is the data management platform? What is the DMP? ". lotame.com.22May 2018, Retrieved on:07-05-18 ]. It allows audience segments to be generated for targeting specific users in an online advertising campaign. DMP may use big data and artificial intelligence algorithms to process big data sets about users from various sources. The DMP is used to organize and monetize data in a real-time bidding system by delegating the data in the real-time bidding system to a global sales platform (DSP). Entities such as nielsen and oracle corporation continue to develop this technology.

Reference to "genomics" means the interdisciplinary field of biology, which focuses on the structure, function, evolution, mapping and editing of genomes. The genome is the complete DNA set of an organism, including all its genes. Unlike genomics, which studies individual genes and their role in inheritance, genomics aims at the centralized characterization and quantification of all genes of an organism, their interrelationships, and the impact on an organism. [ origin: https:// www.who.int/genetics VSgenetics/en/; retrieve 07-07-19 ]. Genes can direct the production of proteins with the help of enzymes and messenger molecules. In turn, proteins constitute body structures such as organs and tissues, and control chemical reactions and transmit signals between cells. Genomics also involves sequencing and analyzing genomes by assembling and analyzing the function and structure of entire genomes using high-throughput DNA sequencing and bioinformatics. [ origin: national human genome institute (11/8/2010), "concise genomics guidelines," genome.gov. search 2011-12-03; concept of genetics (10 th edition) — san francisco: pearson Edudation.2012; culver KW, Labow MA (8November 2002), "Genomics". In Robinson R (ed.). genetics. Macmillan Science Library. Macmillan Reference USA. ]. Advances in genomics have led to a revolution in discovery-based research and system biology to facilitate understanding of the most complex biological systems of the brain. [ origin: kadakkuzha BM, Puthanvetil SV (July 2013), "Genomics and proteomics in solvating library". Molecular BioSystems.9(7): 1807-21 ]. The field also includes the study of phenomena within the genome (within the genome), such as ectopic dominance (the effect of one gene on another), pleiotropic (one gene affects more than one trait), heterosis (heterosis), and other interactions between loci and alleles within the genome.

Reference to "medical diagnosis (" Dx "or" Ds ")" means the process of determining which disease or condition explains a person's symptoms and signs. It is often referred to as diagnosis of an underlying medical context. The information required for diagnosis is typically collected from medical histories and physical examinations of persons seeking medical care. Typically, one or more diagnostic procedures, such as medical tests, are also performed during the procedure. Sometimes, post-mortem diagnosis is considered a medical diagnosis.

Reference to "virtual health assistance" means a virtual and/or online-based messaging service or system that is intended to provide answers in response to queries by a particular patient and/or customer. For example, a "disease-specific robot may answer queries about diseases to patients and doctors, as well as other medical professionals and patient relatives. The child health robot may answer questions about child health for the child's parents regarding a number of symptomsAnd the information of the disease is injected into it ". [ origin:https://chatbotslife.com/artificial-intelligence-based-virtual-health- assistants-the-new-disruptors-42e9f2b44d40(ii) a And (3) retrieval time: 07-07-19]。

Headings are provided herein for convenience, but should not be construed as limiting the disclosure in any way.

The enumerated listing of items does not imply that any or all of the items are mutually exclusive, unless expressly specified otherwise.

It should be understood that the use of specific component, device, and/or parameter names are by way of example only and are not meant to limit the present invention in any way. Thus, the present invention may be embodied in different terms/specific terms used to describe the mechanisms/units/structures/components/devices/parameters herein without limitation. Each term used herein is to be given its broadest interpretation in view of the context in which the term is used.

Term(s) for

The following paragraphs provide definitions and/or background for terms found in this disclosure (including the appended claims):

"including" and "comprising," and variations of these terms, are open-ended and mean "including, but not limited to. When used in the appended claims, the term does not exclude additional structures or steps. Consider the claims so recited: "storage controller … … including a system cache," such claims do not exclude the storage controller from including additional components (e.g., storage channel units, switches).

"configured to". Various units, circuits, or other components may be described or claimed as "configured to" perform a task or tasks. In such a context, "configured to" or "operable to" means that the structure by indicating that the mechanism/unit/circuit/component includes the structure (e.g., the circuit and/or the mechanism) performs the task or tasks during operation. Thus, it may be said that a mechanism/unit/circuit/component is configured to (or operable to) perform a task even when the specified mechanism/unit/circuit/component is not currently operable (e.g., not turned on). Mechanisms/units/circuits/components used with the language "configured to" or "operable to" include hardware-e.g., mechanisms, structures, electronic devices, circuits, memories storing executable program instructions to implement operations, and so on. A mechanism/unit/circuit/component is "configured to" or "operable to" perform a statement of one or more tasks, specifically intended not to cause 35 u.s.c. sctn.112, paragraph six, by that mechanism/unit/circuit/component. "configured to" may also include adapting a manufacturing process to manufacture devices or components suitable for performing or carrying out one or more tasks.

"based on/according to". As used herein, the term is used to describe one or more factors that influence the decision (determination). The term does not exclude other factors that may influence the decision. That is, the decision may be based solely on those factors or at least partially on those factors. Consider the phrase "determine a from B". While B may be a factor that affects the determination of a, such phrases do not exclude that the determination of a is also based on C. In other cases, a may be determined based on B alone.

The terms "a", "an" and "the" mean "one or more", unless expressly specified otherwise.

All terms of exemplary language (e.g., including, but not limited to, "such as," like, "" e.g., "such as," "similar to," etc.) do not exclude any other, potential, unrelated example types; accordingly, the implicit meaning is "exemplary, not limiting … …" unless explicitly stated otherwise.

Unless otherwise indicated, all numbers expressing conditions, concentrations, dimensions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term "about". Accordingly, unless indicated to the contrary, the numerical parameters set forth in the following specification and attached claims are approximations that may vary depending upon at least the particular analytical technique.

The term "comprising" synonymous with "having," "containing," or "characterized by," is inclusive or open-ended and does not exclude additional, unrecited elements or method steps. "comprising" is a term of art used in claim language that means that the named claim element is essential, but that other claim elements can be added and still form a construct within the scope of the claims.

As used herein, the phrase "consisting of … …" does not include any element, step, or ingredient not specified in the claims. When the phrase "consisting of … …" (or variants thereof) appears in a clause of the claim body, rather than following the preface portion, it simply limits the elements presented in the clause; other elements are not excluded from the entire claim. As used herein, the phrases "consisting essentially of … …" and "consisting of … …" limit the scope of the claims to the specified elements or method steps, as well as those that do not materially affect the basic and novel characteristics of the claimed subject matter (see Norian corp.v Stryker corp.,363f.3d 1321,1331-32,70USPQ2d 1508, fed.cir.2004). Moreover, any claim to the present invention claiming an embodiment "consisting essentially of, or" consisting of the particular set of elements of any of the embodiments described herein, should be clearly understood by those skilled in the art to also encompass all possible variations of the scope of any of the described embodiments that are individually exclusive (i.e., "consisting essentially of … …") subsets of functions or functional combinations thereof, such that each of these multiple exclusive variations consists essentially of any subset of functions and/or functional combinations of any of the elements of any of the described embodiments, excluding any other matter not explicitly stated herein. That is, it is contemplated that it will be apparent to those skilled in the art how to create alternative embodiments of the present invention that simply consist of a certain functional combination of elements of any described embodiment, excluding any other combinations not yet set forth herein, and that the present invention therefore covers all such exclusive embodiments as if they were all described herein.

With respect to the terms "comprising," "consisting of … …," and "consisting essentially of … …," where one of the three terms is used herein, the disclosed and claimed subject matter can include the use of the other two terms. Thus, in some embodiments that are not explicitly recited, any instance of "comprising" may be replaced with "consisting of … …," or alternatively, with "consisting essentially of … …," and thus, for the purposes of the claims to support and interpret a formatting claim of "consisting of … …," such replacement operates to create additional alternative embodiments that consist essentially of only the elements recited in the original "comprising" embodiment, excluding all other elements.

Furthermore, any claim limitations expressed in functional limitation terms encompassed by 35 USC § 112(6) (post AIA 112(f)) having the preamble of invoking the closure term "consisting of … …" or "consisting essentially of … …" should be understood to mean that the corresponding structure disclosed herein defines the exact limits of what constitutes or consists essentially of embodiments of the claimed invention, excluding any other elements that do not materially affect the intended purpose of the claimed embodiments.

Devices or system modules that are in at least general communication with each other need not be in continuous communication with each other, unless expressly specified otherwise. Further, devices or system modules that are at least generally in communication with each other may communicate directly or indirectly through one or more intermediaries. Moreover, it should be appreciated that any system components described or named in any embodiment or claimed herein may be grouped or grouped (and implicitly renamed accordingly) in any combination or subcombination, as may be imagined by one skilled in the art, as appropriate for a particular application, and still be within the scope and spirit of the claimed embodiments of the invention. For example, if the invention is a controller for motors and valves, and the embodiments and claims express these components as being individually grouped and connected, applying the foregoing will mean that such invention and claims will also implicitly cover valves grouped within motors, and controllers being remote controllers that are not directly physically connected to motors or built-in valves, so that the claimed invention is intended to cover all ways of grouping and/or adding intermediate components or systems that still substantially achieve the intended effects of the invention.

A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the variety of possible embodiments of the present invention.

As is well known to those skilled in the art, many careful considerations and compromises must generally be made when designing an optimal fabrication for a commercial implementation of any system, particularly the embodiments of the invention. Commercial implementations consistent with the spirit and teachings of the invention may be configured as desired for particular applications, whereby any aspect, feature, function, result, component, method, or step of the teachings related to the described embodiments of the invention may be suitably omitted, included, adapted, mixed and matched, or modified and/or optimized by those skilled in the art, using their average skills and known techniques, to achieve a desired implementation to meet the needs of a particular application.

A "computer" may refer to one or more devices and/or one or more systems that are capable of accepting a structural input, processing the structural input according to prescribed rules, and producing results of the processing as output. Examples of the computer may include: a computer; a stationary and/or portable computer; a computer having a single processor, multiple processors, or multi-core processors, which may run in parallel and/or not; a general-purpose computer; a supercomputer; a mainframe; a super mini-computer; a small computer; a workstation; a microcomputer; a server; a client; an interactive television; a network device; telecommunication equipment with network access; a hybrid combination of computer and interactive television; a portable computer; a tablet Personal Computer (PC); personal Digital Assistants (PDAs); a portable telephone; special purpose hardware that simulates a computer and/or software, such as a Digital Signal Processor (DSP), Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), application specific instruction-set processor (ASIP), chip, chips, system on a chip, or chipset; a data acquisition device; an optical computer; a quantum computer; a biological computer; and generally, means that can accept data, process data according to one or more stored software programs, generate results, and generally comprise input, output, storage, computation, logic, and control units.

Those skilled in the art will appreciate that some embodiments of the disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like, where appropriate. Embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

"software" may refer to prescribed rules for operating a computer. Examples of software may include: code segments in one or more computer-readable languages; graphics and/or text instructions; an applet; pre-compiling the code; an transliteration code; compiling the codes; and a computer program.

Although embodiments herein may be discussed in terms of a processor having a certain number of bits of instruction/data, one skilled in the art will appreciate other embodiments that may be suitable, such as 16-bit, 32-bit, 64-bit, 128-or 256-bit processors or processes, which may generally be used alternatively. Where a specified logical sense is used, the opposite logical sense is also intended to be included.

The example embodiments described herein may be implemented in an operating environment that includes computer-executable instructions (e.g., software) installed on a computer, in hardware, or in a combination of software and hardware. The computer executable instructions may be written in a computer programming language or may be embodied in firmware logic (firmware logic). Such instructions, if written in a programming language conforming to a recognized standard, may be executed on a variety of hardware platforms and for interface to a variety of operating systems. Although not so limited, computer software program code for carrying out operations of aspects of the present invention may be written in any combination of one or more suitable programming languages, including an object oriented programming language and/or a conventional procedural programming language, and/or a programming language such as hypertext markup language (HTML), dynamic HTML, extensible markup language (XML), extensible stylesheet language (XSL), document style semantics and specification language (DSSSSL), Cascading Style Sheets (CSS), Synchronized Multimedia Integration Language (SMIL), Wireless Markup Language (WML), Java.TM., Jini.TM., C, C + +, Smalltalk, UNIL, UNIX Shell, Visual Basic or Visual Basic script, Virtual Reality Markup Language (VRML), Coldfusion.TM, or other compilers, assemblers, interpreters, or other computer languages or platforms.

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

A network is a collection of links and nodes (e.g., multiple computers and/or other devices connected together) arranged such that information may be communicated from one part of the network to another over the multiple links and through the various nodes. Examples of networks include the internet, a public switched telephone network, a global telex network, a computer network (e.g., an intranet, an extranet, a local area network, or a wide area network), a wired network, and a wireless network.

The internet is a global network of computers and computer networks that is arranged to allow simple and stable exchange of information between computer users. Hundreds of millions of people worldwide can access computers connected to the internet through Internet Service Providers (ISPs). A content provider (e.g., a website owner or operator) places multimedia information (e.g., text, graphics, audio, video, animation, and other forms of data) on the internet in a specific location called a web page. A web site includes a collection of connected or otherwise related web pages. The combination of all web sites on the internet and their corresponding web pages is commonly referred to as the World Wide Web (WWW) or simply the web.

Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine (a machine), such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

Further, although process steps, method steps, algorithms or the like may be described in a sequential order, such processes, methods and algorithms may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any practical order. Further, some steps may be performed simultaneously.

It will be apparent that the various methods and algorithms described herein may be implemented by, for example, a suitably programmed general purpose computer and computing device. Typically, a processor (e.g., a microprocessor) will receive instructions from a memory or similar device and execute those instructions to perform a process defined by those instructions. In addition, programs implementing such methods and algorithms may be stored and transmitted using a variety of known media.

When a single device or article is described herein, it will be readily apparent that more than one device/article (whether or not they cooperate) may be used in place of a single device/article. Similarly, where more than one device/article is described herein (whether or not they cooperate), it will be readily apparent that a single device/article may be used in place of the more than one device/article.

The functionality and/or the features of a device may be alternatively embodied by one or more other devices which are not explicitly described as having such functionality/features. Thus, other embodiments of the present invention need not include the device itself.

The term "computer-readable medium" as used herein refers to any medium that participates in providing data (e.g., instructions) that may be read by a computer, processor or similar device. Such a medium may take many forms, including but not limited to, non-volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks and other persistent memory. Volatile media include Dynamic Random Access Memory (DRAM), which typically constitutes a main memory. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise a system bus coupled to the processor. Transmission media can include or convey acoustic waves, light waves and electromagnetic emissions, such as those generated during Radio Frequency (RF) and Infrared (IR) data communications. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EEPROM, a removable medium, a FLASH memory, a "memory stick", any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read.

Various forms of computer readable media may be involved in carrying a sequence of instructions to a processor. For example, the sequences of instructions may be (i) transferred from the RAM to the processor, (ii) carried on a wireless transmission medium, and/or (iii) formatted according to a variety of formats, standards, or protocols (e.g., bluetooth, TDMA, CDMA, 3G).

In describing databases, one of ordinary skill in the art will appreciate that (i) alternative database structures to those described may be readily employed and (ii) memory structures other than databases may be readily employed. Any schematic and accompanying description of any example database presented herein is an example arrangement for stored representation of information. Any number of other arrangements may be employed in addition to those suggested by the illustrated table. Similarly, any illustrated database entries represent only exemplary information; those skilled in the art will appreciate that the number and content of the items may be different than shown here. Further, while the database is illustrated as a table, object-based models can be used to store and manipulate the data types of the present invention, and as such, object methods or behaviors can be used to implement the processes of the present invention.

A "computer system" may refer to a system having one or more computers, where each computer may include a computer-readable medium embodied as software to operate the computer or one or more components thereof. Examples of computer systems may include: distributed computer systems for processing information through computer systems linked by a network; two or more computer systems connected by a network for transmitting and/or receiving information between the computer systems; a computer system including two or more processors within one computer; one or more devices and/or one or more systems that can accept data, process data according to one or more stored software programs, generate results, and generally can include input, output, storage, algorithms, logic, and control units.

A "network" may refer to a plurality of computers and associated devices that may be connected by a communications facility. The network may involve permanent connections, such as cables, or temporary connections, such as those made through telephone or other communication links. The network may also include hard-wired connections (e.g., coaxial cables, twisted pair wires, optical fibers, waveguides, etc.) and/or wireless connections (e.g., radio frequency waveforms, free-space optical waveforms, acoustic waveforms, etc.). Examples of networks may include: the Internet, such as the Internet; an intranet; a Local Area Network (LAN); a Wide Area Network (WAN); and a combination of networks (e.g., the internet and an intranet).

As used herein, a "client" application should be broadly construed to refer to an application, a page associated with the application, or some other resource or function that is called by a client's request to the application. As used herein, "browser" is not intended to refer to any particular browser (e.g., Internet Explorer, Safari, FireFox, etc.), but should be broadly construed to refer to any client rendering engine that can access and display Internet-accessible resources. A "rich" client typically refers to a non-HTTP based client application, such as an SSH or CFIS client. Furthermore, while client-server interaction is typically done using HTTP, this is not a limitation. Client server interactions may be formatted to conform to Simple Object Access Protocol (SOAP) and transmitted over HTTP (over the public Internet), FTP, or may use any other reliable transmission mechanism (e.g., ibm.rtm.m. qseries.rtm. technology and CORBA for transmission over enterprise intranets). Any application or function described herein can be implemented as native code by providing a hook (hook) to another application, by facilitating the use of the mechanism as a plug-in, by linking to the mechanism, etc.

The exemplary network may operate using any of a variety of protocols, such as Internet Protocol (IP), Asynchronous Transfer Mode (ATM), and/or Synchronous Optical Network (SONET), User Datagram Protocol (UDP), IEEE 802.x, and the like.

Embodiments of the present invention may include apparatuses for performing the operations disclosed herein. The apparatus may be specially constructed for the desired purposes, or it may comprise a general-purpose device selectively activated or reconfigured by a program stored in the device.

Embodiments of the invention may also be implemented in one or a combination of hardware, firmware and software. They may be implemented as instructions stored on a machine-readable medium, which may be read and executed by a computing platform to perform the operations described herein.

More specifically, as will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," module "or" system. Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable media having computer-readable program code embodied therein.

In the following description and claims, the terms "computer program medium" and "computer-readable medium" may be used to generally refer to media such as, but not limited to, removable storage drives, hard drives installed in a hard disk, and the like. These computer program products may provide software to a computer system. Embodiments of the present invention may be directed to such computer program products.

An algorithm is here, and generally, considered to be a self-consistent sequence of acts or operations leading to a desired result. These include physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. It should be understood, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities.

Unless specifically stated otherwise, and as is apparent from the following discussion and claims, it is appreciated that throughout the description, discussions utilizing terms such as "processing," "computing," "calculating," "determining," or the like, refer to the action and/or processes of a computer or computing system, or similar electronic computing device, that manipulate and/or transform data represented as physical, such as electronic, quantities within the computing system's registers and/or memories into other data similarly represented as physical quantities within the computing system's memories, registers or other such information storage, transmission or display devices.

Further, the phrase "configured to" or "operable to" may include a general-purpose structure (e.g., a general-purpose circuit) that is manipulated by software and/or firmware (e.g., an FPGA or a general-purpose processor executing software) to operate in a manner that enables performance of the task at issue. "configured to" may also include adjusting a manufacturing process (e.g., a semiconductor processing facility) to fabricate devices (e.g., integrated circuits) suitable for performing or carrying out one or more tasks.

In a similar manner, the term "processor" may refer to any device or portion of a device that processes electronic data from registers and/or memory to transform that electronic data into other electronic data that may be stored in registers and/or memory. A "computing platform" may include one or more processors.

Embodiments within the scope of the present disclosure may also include tangible and/or non-transitory computer-readable storage media for carrying or having computer-executable instructions or data structures stored thereon. Such non-transitory computer-readable storage media can be any available media that can be accessed by a general purpose or special purpose computer, including the functional design of any special purpose processor as described above. By way of example, and not limitation, such non-transitory computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer-executable instructions, data structures, or processor chip design. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination thereof) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such connection is properly termed a computer-readable medium. Combinations of the above should also be included within the scope of computer-readable media.

Although non-transitory computer readable media include, but are not limited to, hard drives, optical disks, flash memory, volatile memory, random access memory, magnetic memory, optical memory, semiconductor-based memory, phase change memory, optical memory, periodically refreshed memory, and the like, non-transitory computer readable media do not include purely transitory signals per se; i.e. the medium itself is temporary.

The challenging and inefficient nature of traditional HMOs may include complex billing, insurance and new patient inclusion procedures. When combined with extremely complex therapy and treatment requirements, it can be difficult for customers and/or patients to participate in such HMOs, thereby making such persons often seek realistic and reliable cost-effective alternatives. Moreover, such HMOs may not be uniformly implemented, even with due consideration to advanced computer science-based data analysis techniques including artificial intelligence ("AI"), machine learning, neural networks, image recognition, blockchain-based techniques, artificial intelligence-based virtual health assistance, Data Management Platforms (DMPs), genomics, and the like, to simplify existing processes to achieve cost benefits.

The system herein transforms a highly decentralized, hospital-centric healthcare delivery system into a patient-centric, single, universally federated, global healthcare system by providing high-quality care and revolutionary intelligent digital solutions that deliver microservice software, processing, and medical devices to patients at affordable or reduced costs. The system enables digital conversion techniques including artificial intelligence and machine learning for innovative algorithms, third party data for insight (insight or insight) and outcome yield (outtome), bionics and biometrics for cryptographically secure Protected Health Information (PHI) and Personally Identifiable Information (PII), and block chain techniques to protect Distributed Ledger Technology (DLT) transactions. Its multi-regional cloud infrastructure throughout the world provides secure web services and smartphone portals where suppliers and equipment manufacturers get incentives, while patients, participants and other users get digital currency tokens to pay their healthcare fees at a lower price. The platform will test continuously and independently; the tuning and implementation of healthcare devices, processes, software tools, and newer digital emerging technologies that are the leading edge of known healthcare delivery.

The system, referred to as "a-Medicare," converts and makes obsolete many processes, services and transactions by employing newer digital technologies, single and blockchain databases, machine learning, third party data, patient data analysis and artificial intelligence to obtain accurate insight into and outcome outcomes from drug use, diagnostics, healthcare and patient health lifestyles.

Fig. 1 illustrates a schematic diagram of the interaction of a-Medicare's patient-centric architecture 100, including integration with cloud computing (AWS)102, cloud computing (HEROKU)104, participants 106, a-Medicare application 108, and customer access tools 110. Since the system mimics the functionality of an entire healthcare system, a-medical participants 106 include, but are not limited to, doctors, nurses, medical technicians, insurers, IPA, emergency personnel, hospitals, medical laboratories, researchers, radiologists, pharmaceutical companies, drug manufacturers, medical device manufacturers, government regulatory agencies, auditors, and network security experts. Each participant category has a personalized portal in which relevant information is displayed. Two-way interaction also takes place in each individual's portal. However, some participants may be passive participants, such as databases, where information simply travels when queried from the applications of the system.

The A-medical application 108 provides a full set of services for the healthcare industry and includes, but is not limited to, appointment scheduling, medical billing, hospital management, medical device management, health tracking and diagnosis, electronic medical and health records, practice management, patient master indexing, patient portals, remote patient monitoring, clinical decision support, fitness and lifestyle management, nutrition and dietary services, disease management, feminine health, drug management, telemedicine, medical imaging, and reward-based programs, such as advertising.

The client access tool 110 may include, but is not limited to, a web browser and a smart phone. However, the system may also be integrated with other technologies, including professional medical devices, but also with personal electronic and internet of things devices, such as wearable technologies, voice-assisted technologies, and robotic assistance.

Fig. 2 illustrates an example "cloud" based system and the interaction of a user's wearable device on the system. The software and hardware infrastructure performs network-connected command, control, and continuous monitoring (C3M) 202 of the customer hospital operations and tracks and analyzes the user's health data 208 using the internet of things (IoT) and the bionic device 204 worn by the patient 206. C3M202 obtains and processes real-time data 216, such as location, charts, doctors, providers, and medical insurance, of patient 206 at the time of first symptom occurrence. The a-Medicare command center 214 includes a federated cloud database 218 that interacts with patient data 216 that is continuously monitored by C3M 202. The real-time changes result in alerts being pushed to medical personnel and contracting healthcare professionals 212. In addition, wearable device 204 includes a plurality of sensors 210 that sense sudden falls, blood pressure, glucose levels, and body temperature.

Fig. 3 is an exemplary flow diagram of notification system 200 involving wearable device 204. A patient 206 is shown wearing a wearable device 204 with a trigger 220. The system 200 detects whether a fall 222 has occurred. If a sudden fall 222 has occurred, the system sends a notification 224 to C3M202, which in turn notifies the medical professional 212 of the C3M. If no sudden fall is detected 222, the system asks whether the reading is out of range 226. If the reading is out of range 226, the system 200 sends a notification 224 to C3M, which C3M in turn notifies the medical professional 212. If the reading is not out of range, a medical professional 212, such as a field provider, is contacted. In some embodiments, the IoT sensor readout information 210 will also be integrated with a home portal 228, which can direct the robotic assistant 230 to register and, if necessary, contact the medical professional 212.

To provide continuous monitoring of patient health, internet of things (IoT) devices 204 are implemented to provide continuous feedback, affecting different executable tasks in the system. These IoT devices 204 can be wearable devices (similar to fitsit or Apple Watch) and biomimetic nano-devices, such as liquid chips embedded in the skin of a patient, whose electrical energy is derived from skin temperature. These devices 204 securely store selected patient "diary" data, such as PII and PHI. Once the nano-or IoT device 204 approaches the vicinity of the secure Wi-Fi network, it will automatically connect and upload the new data to the central database, as illustrated in fig. 4 by the patient's internet of things device and autonomous server communication. The central database 218 is continuously updated with the patient's daily activities (e.g., exercise, drug or medication use, diet, and other behavioral data 208). The use of the biomimetic and wearable device 204 employs intelligent software tools and notification protocols 224 that are linked to data warehouses, third party data, and network intelligence to identify potential failures of the device (IoT) and changes in the patient's medical data long before symptoms occur.

The autonomous AI/ML algorithm 234 is also applied on cloud servers, such as C3M 202. These algorithms ping the patient's IoT device 204 every 30 seconds. If the patient's device does not respond, the system pings a microservice and sends a flash on the C3M screen, notifying the operator that the device may fail and notifying the nearest linesman to visit the patient. These algorithms verify that the patient's temperature, blood pressure, glucose and other biometric data are reading abnormally and pass this information to C3M and medical personnel.

Network security is implemented using blockchains, immutable ledgers, and hashing techniques on selected Personal Identifiable Information (PII), Protected Health Information (PHI), diagnostics, and DNA to comply with HIPAA and other regulatory agencies, as discussed in fig. 9 and below.

The exemplary embodiment implements federated database 302, as shown in FIG. 5. Federated database 302 may also include a localized database 312 or be connected through an internet gateway 310 to public and private databases 318, blockchain databases 306, cloud-based data warehouses 304, and a single central enterprise database 308 for the a-Medicare system. The information of the federated database 302 is integrated through the use of machine learning algorithms 320, operations and processes in the geographic region for performance, ethical practices, local customs, local medical practices, and finer grained patient data. These data and insights are presented to the doctor and decision maker, for example, in the doctor's office 316, on a large display panel or personal device 314 (e.g., laptop, desktop with graphical user interface), or with a tablet (e.g., iPad or other tablet-type device).

The system establishes a global consortium with insurance companies, service providers, pharmaceutical manufacturers, equipment manufacturers, financial institutions, insurers, governments and assistance organizations to establish policies and standards with increasingly complex global healthcare practices. This allows the systems to be cross-linked over a wide range of technologies to form a collaborative platform that, in some embodiments, allows inputs to be converted into a common protocol for processing by the system using raw data associated with each of the insurance companies, service providers, pharmaceutical manufacturers, equipment manufacturers, financial institutions, insurers, governments and assistance organizations.

The system creates a network 400 of "express providers" 402, consisting of front-line personnel, such as nurses, doctors, Emergency Medical Technicians (EMTs), etc., near the patient's home. Figure 6 illustrates an exemplary embodiment of an a-medical fast provider network. The "express providers" 402 may provide immediate care to patients during emergencies when the nearest hospital, medical clinic, or healthcare provider facility is miles and hours away. The system records the geographic location of each user device, including that of the patient and service provider, and allows the system to match nearby service providers and patients, while filtering out providers that may be helping other patients or failing to meet the required response time. This also eliminates the barrier to dispatch service providers immediately, as the system monitors the location of the service provider in real time, which the dispatcher cannot do, as multiple geographic locations may move around and the nearest service provider may change in seconds.

C3M202 receives a-Medicare fast provider network data and processes the information for autonomous notification system 404. The autonomous notification system 404 can pair patient location with members 402 of the a-Medicare network. It may also provide the member 402 with patient data, driving directions, and suggest necessary services, recommend type of care, and report services provided.

In addition to using geographic location to match service providers, the system incorporates an early warning and tracking system to monitor organ donors worldwide and record organizational work for quick and safe preparation, transport and transplantation to patients on receiving an organ top priority list.

Some embodiments employ an early warning tracking system 500, as shown in fig. 7, to monitor organ donors. The A-Medicare global network 502 communicates bi-directionally with the C3M 202. The a-Medicare global network 502 monitors the upcoming availability or organ 504. When organs become available from the organ donor 508, the autonomic notification service 506 triggers notifications that are pushed to interested parties, including the members 402 of the a-Medicare network and the organ recipients (patients 206). The autonomic notification service 506 relies on a machine learning algorithm 510 that processes which recipient will be matched to receive the organ by receiving an upcoming notification of the organ donation from the member network, pairing the patient in the prioritized list with the donor and the nearest location, identifying and matching the patient's biometric data with the organ data, processing and coordinating the transport of the organ and/or patient to the most qualified hospital and the physician specialist who can perform the donor transfer, providing all chart data to all involved parties, coordinating the necessary services, and reporting the services provided. The machine learning algorithm may also modify the recommended treatment based on the likelihood of a donor match or whether no match is imminent, and then recommend and/or apply other treatment methods.

In some exemplary embodiments, as shown in fig. 8, a laptop, desktop, or smart device 602, such as a smartphone or tablet, includes a client-side web browser, and the smartphone application includes a client-side primary "engine" developed around a patient-centric interface using a combination of server-based, browser-based, and machine-learning-based algorithmic software 604 that uses Python, SQL, node. Providers, patients, insurers, pharmacists, administrators, and other users will have access to the secure browser-based web client and smartphone native application, implementing the unique artificial intelligence-based architecture and services of a-Medicare.

In an exemplary embodiment of the system showing the system's interaction with the hospital, doctor's office, insurer and patient interfaces 616, as shown in fig. 8, information is extracted from the partner databases including the federated database 302 stored on the cloud, the data warehouse 304 stored on the cloud, the single database 308 and the blockchain database 306. The information is transmitted over a network to a user's modem, router, or other network connection 610. Which is then stored on a local data source 612 and displayed on the user's device 614.

The system includes a rule-based panel system. By logging on to a strategically designed rule-based panel system, the patient or administrator can manage the doctor's appointments, verify the patient's medical records and providers, select the best and cheaper medical insurance, hospital services, surgery, doctor's visit, medication, doctor's specialist, and pharmacy.

Fig. 9 illustrates encryption of data within a system. Using the custom cryptographic hash algorithm 702, the client engine encrypts sensitive transaction data 704, such as insurance, diagnostics, finance, Personally Identifiable Information (PII), and Protected Health Information (PHI), as it is used by users in various page navigations through the a-medical network service. The data 704 is transmitted as encrypted data 706 that is transmitted over the network. The client engine randomly updates the encryption key at different times to prevent hackers from knowing the exact key at these random times.

Depending on how the user navigates or uses a-Medicare web services or smartphone applications, hundreds of autonomous microservices (e.g., "daemons" in Unix), or microrobots (bots) work continuously in the background, well known tasks are performed such as searching for or detecting anomalous network security activities (e.g., lasso, DDoS, and phishing software that will interrupt, kill or blacken windows client services or inject themselves into other applications of various services and devices of the host operating system).

The system embeds cognitive technology into the client "engine" as the user navigates through the various pages of an a-medical web service application or smartphone application in concert with server-based services and processes. The client "engine" will detect and collect context sensitive words and phrases on the current page of the network or application into a local cache, and then randomly destroy or update this cache when the specific tasks of the network service are completed.

The a-Medicare platform collects information into a single data warehouse using locally developed encryption and hashing techniques, with prior user consent (via a pop-up or dialog box) or smart contracts. This data can be collected and presented in a large display screen or iPad type device for the user's insight, audit and outcome yield for further analysis by physicians and decision makers. The system securely queries a single and blockchain validated database cluster using custom hashing and encryption techniques based on thousands of pre-created scripts and microservices that are machine learning based, well documented, and easy to use by any type of user.

For performance, database queries are redirected by the federated master agent for the single and blockchain database region locations of the partitions (as an example, sydney), where a web service client or smartphone device is used based on its location.

In some exemplary embodiments, the system combines federated database and blockchain techniques, as can be appreciated in FIG. 10. The a-Medicare platform will consist of several federated databases 802, data warehouses 804, and blockchain databases 806 that can be built or populated with health data (e.g., epidemiological studies, disease and biohazard monitoring) as well as other data from a variety of sources, including local data, PII, PHI, diagnostics, pharmaceutical, medical and drug research, peer-to-peer networks, insights, charts, patients, user profiles, metadata, and data automatically transmitted by nano-and internet-of-things devices. The data is synchronized in real-time across platforms. For example, Pseudo-example Code (Pseudo Sample Code) to synchronize data from the CDC:

these databases will be physically hosted in highly secure cloud infrastructures in various regions around the world, using the additional layer of network security of a-medical, which is almost impossible to hack into.

The blockchain database captures the general ledger data as another technique to hide PII, PHI, diagnostic data, financial and other healthcare data.

An example of generating Pseudo-identical Data Elements (Pseudo Same Data Elements) for a foundational block and subsequent transactions is as follows:

fig. 10 also shows a system architecture in which a machine learning algorithm, neural network, and other programming framework 808 extracts information from federated database 802 and data from established sources 810, including public databases, social media, corporate data, medical journals, drug data, medical device manufacturer data, and insurance data, which are in turn processed according to modules 812 for processing insights, outcome outcomes, advertising data, treatments, rewards, and diagnoses, and then sent to the appropriate microservices 814, whereby the outcome outcomes are communicated to the appropriate parties 816, including users, providers, advertisers, patients, physicians, pharmaceutical industry workers, device manufacturers, organ donors, enterprise donors, charities, and medical researchers.

In some embodiments, the a-medical system provides a real-time decision support system consisting of thousands of queries and services, which are based on machine learning algorithms, that are displayed into a variety of large displays and iPad/tablet type devices. Machine learning algorithms automatically learn and improve the process from experience without explicit programming or manual provision of other data.

The iPad/tablet device is used by doctors and nurses for C3M type monitoring and quick response to provide services. These display devices display patient charts, patient-physician-nurse interactions, drug administration patterns, drug usage, patient monitoring, upcoming assays, diagnostic data, genetic testing, personalized digital health plans, and other healthcare information.

The system provides information about the self-treatment of the disease and improves communication between the patient and the care professional so they can manage the patient's health in the home. Capturing the process and analyzing the results by remote monitoring will improve home health management and proper care of the medication.

In many embodiments, medical records, diagnostic data, and charts are protected at a high level. The A-Medicare system implements Confidentiality, Integrity, and Availability triplets, called network security "CIA". CIA protects the patient's PII, PHI, diagnostic, insurance and financial data and makes the data available when needed.

Fig. 11 illustrates an exemplary embodiment of the system. The system shows a federated database 302, a warehouse database 304, a single database 308, and a blockchain database 306, with autonomous machine learning algorithms 902 integrated onto the servers. Algorithm 902 is configured to provide and update personal medical records, charts, histories, and archives as well as documentation. Data from the algorithm 902 is received by a user interface at the patient's home 916 over a network connection 910 and stored as local data 912. This information is then displayed on the user device 914, which may be a smartphone in some embodiments.

Personal medical records, charts, historical archives, and doctor's patient-meeting documents are securely kept in the single database 308 and blockchain database 306 databases, both stationary and on-route, using machine learning algorithm 902. The confidential data can only be accessed through two-step authentication over advanced encryption techniques and network security policies and other government mandated policies (e.g., HIPAA) to protect the PHI and PII of the patient. In addition, the plaintext data can be obscured by algorithms designed for A-medical machine learning before it is saved to the appropriate database. The translation code is similar to SALT in the encryption of the obscured plaintext data. This process is almost impossible to hijack or intercept while the data is in transit to its final destination. An exemplary pseudo-example code is provided to add additional security:

the secure healthcare data can be accessed by browser and smartphone based applications and role and machine learning algorithm based authorization and two-step authentication when seeking to make an appointment with a healthcare practitioner.

Some embodiments of the invention include advertising, web services, and smartphone application content to keep users engaged and thereby encourage users to learn their health, which is intended to promote a healthier lifestyle. One of the ways the system performs this is, inter alia, through a reward system that supports advertising.

The ad pop-up dialog box of a-medical is triggered and presented to the web service and smartphone client based on the user's preferences, posts, profiles, words, phrases, and health information and device location. These insights or results are the result of custom designed machine learning algorithms that learn the user's accurate and in-depth visual understanding and are the result of extractions from single data warehouses, blockchain databases, and other common records.

Js, the client application displays customized ad pop-up dialog boxes based on user insights. The pop-up dialog box is designed to be less intrusive so it does not affect or block what the user is reading. In some embodiments, by clicking on the ad pop-up dialog, the A-Medicare awards a portion of the ad revenue to the user as A-Medicare encrypted monetary tokens. The number of seconds and minutes the user spends on the advertiser's corporate website and the types of content of interest to the user will be collected and stored to a data repository for later insights.

Rewarding users a-Medicare encrypted monetary tokens encourages users to search for more information offered free of charge by the a-Medicare platform. User likes, comments, opinions, ideas, posts, and suggestions will help to improve healthcare, medicine, medical products, and healthcare-related services in the future. In addition, the system motivates the user to further study the information, such as self-management of small diseases or ailments. Compensation from interaction with the advertisement, whether encrypted tokens or another type of digital credit, may be pooled into a single account.

In addition to the user being compensated for viewing the advertising content, a percentage of advertising revenue supports other aspects of the a-medical system. A-medical ' after the fact ' insurance type payments absorb the cost and fund the patient's surgery. A-medical initially fundes expenses while obtaining funds from good donors, charitables, and users who wish to share excess tokens with patients. Users who donate credit points to others and are considered good performers will obtain additional tokens.

Some embodiments relate to integration with virtual assistance technologies including, but not limited to, voice assistance and robotics, using blockchain and machine learning techniques to convert medical records and diagnoses to "Siri" or "Alexa" like voice assistance. The system may include a robot, as shown in fig. 12 and 13, functioning as a personal health assistant. In addition, a-Medicare may collaborate with third party robot manufacturers whose robots meet stringent specifications.

The bot 1002 may be configured to understand english commands and respond to the commands accordingly, e.g., open a door 1004 for home healthcare services, open a television 1006 for news and other entertainment. These robots 1002 may also call 911, RMT, a healthcare provider, or a supplemental medication 1008. It may remind the patient to schedule medication 1012, prepare certain drinks, remove items from the refrigerator, heat food 1014, and manage other daily tasks to serve his/her owner, including measuring temperature 1016. Embedded in the memory of the robot 1002 are thousands of a-Medicare designed machine learning algorithms 1018 that automatically learn and improve experience without explicit programming of manually entered data or procedures. The algorithm 1018 also communicates bi-directionally with the a-medical cloud infrastructure 1020.

Figure 13 illustrates patient and robot communication. Microphones with bluetooth or WIFI connectivity are strategically installed throughout the patient's home 1102. All devices automatically connect to a specialized robotic home portal 1104 (much like a WIFI router). When service is needed, the patient 1106 speaks commands 1108 in english for the medical robot 1002. If received within hearing range or via WIFI of the robotic home portal 1104, the robot 1002 may hear the "raw" command 1108. Robot 1002 receives commands 1108, interrogates its CPU (computer central processing) memory and compares english commands 1108 from robot 1002 and the a-medical joint database and thousands of AI (artificial intelligence) based machine learning processes 1110 internal to C3M 202. The robot interprets the commands 1108 and responds 1112 to the patient 1106 using speech synthesis through its own speaker. The robot performs actionable tasks 1114 as required by the patient. In some embodiments, the user 1106 also wears a wearable device with a trigger 220 that sends a signal to the robot 1002 without using voice commands.

All commands 1108 from the patient 1106, their responses 1112, and tasks 1114 performed as heard by the robot 1002 come from a machine learning algorithm 1110, either in the microprocessor of the robot 1002 or from an a-medical server based machine learning algorithm 1018 accessing a federated database and a-medical cloud infrastructure 1020. All other commands 1108 and corresponding task executions 1114 are learned without further programming.

In some embodiments, the system creates and utilizes thousands of revolutionary and novel machine learning algorithms 1202 with respect to the process and machine learning program repository, as can be appreciated in fig. 14. These algorithms run on third party data 1204 that can track abuse, underuse, or overuse of prescription drugs, detect equipment system failures before they occur, perform unnecessary duplication in healthcare practice, poor communication strategies, and inefficiencies. The algorithm 1202 merges publicly available and third party healthcare data 1204 and a-Medicare federated database 802, blockchain 806, and repository 804 to continually update, clean, load, and convert transactions into the data repository 804 using the third party data 1204 to provide a solution for insight and outcome yield 1206. They identify safe, effective, patient-centric, timely, efficient, and fair procedures and care. They can also easily link patients with healthcare practitioners and service providers.

The algorithm also maps multiple autonomous database systems into a single federated database 1208, integrating several different and unstructured database systems into a display useful to practitioners, insurers, administrators, and patients. This allows the system to take raw data from many servers in different formats, convert it to a single format that can then be applied throughout the system. Machine learning algorithm 1202 is also bi-directionally integrated with microservice 1208 and is affected by monitoring system 1210.

FIG. 15 illustrates the integration of an autonomous machine learning algorithm with various functions of the system. Data from various a-Medicare processes and other third party sources 1302, both public and private (with prior intelligent contracts 1304), is collected into the secure data warehouse 304 and federated database 302. Thousands of machine learning algorithms 1306/1308/1310 are created by a-medical data and machine learning scientists and published in a user-friendly interface accessible to authorized subscribers, researchers, doctors and other participants. The autonomous machine learning algorithm 1306 collects this data and, through the API, may be accessed by pharmaceutical companies and device manufacturers in addition to subscribers, researchers, and doctors.

This data warehouse 304 using third party technology is continually updated and new information from the autonomous machine learning algorithm 1308 (e.g., patient medical history, physical examination, diagnostic tests, and hypothetical diagnoses) is added. The new data is further collected, verified and cleaned by using machine learning and best practices, so that medical diagnosis, drug use and other nursing are more accurate. These data can be accessed using thousands of off-the-shelf machine learning algorithms 1310 to predict the participant's symptoms, genetic characteristics, and how it will react to new drugs and revolutionary care or surgery.

An exemplary aspect of the system is that the use of data may affect the recommended treatment for the patient, which may include variables such as availability of drugs, matching organs, available medical supplies, location of organs, and medical competency in some regions of the country. This allows the machine learning algorithm to provide real-time recommendations on the actually available treatments and therapies, which can be administered to a particular patient in a particular area at any given time.

FIG. 16 illustrates an exemplary embodiment of an autonomous machine learning algorithm integrated with various functions of the system. Using third party, federated data warehouse 304, blockchain database 306, and artificial intelligence, in conjunction with up-to-date machine learning algorithm 1406, can provide more accurate insights and outcome outcomes for data scientists, system analysts, healthcare professionals, equipment manufacturers, and pharmaceutical manufacturers. The results and resulting output using newer digital conversion tools can prevent disease, create new and better drugs, provide new methods of analytical diagnostic testing, accurately identify symptoms, and provide accurate care and its cost, and impact the invention of new medical devices. Other algorithms 1408 provide clearer data that is easier to implement in a unified protocol of the system. The data output from the algorithm 1408 may be sold to device manufacturers, hospitals and suppliers, governments, insurance entities and marketers for the development of better pharmaceuticals, better medical device manufacture, and better healthcare treatment and procedures. In addition, some algorithms 1410 encourage healthier lifestyles to limit hospitalization, limit doctor visits, reward rewards such as tokens, and encourage the use of excess tokens to increase the health of an unfortunate user.

In the long term, the incorporation of such newer digital conversion tools saves costs to governments, insurers, hospitals, independent suppliers, and patients. These updated sets of digital transformation tools accessing the federated database provide all the necessary information to comply with PHI, PII, HIPAA, network security policies, and other government policies. Information technology and software engineers may use digital conversion tools to develop safer code applications and software modules based on blockchains to manage doctor's appointments, insurance, suppliers, or hosted services, such as surgery, doctor's visit, ICU, ER, drugs, experts, and drugs. In addition, these tools provide a comparison of quality care, various services, insurance premiums, hospitalization costs, and the correct medications for the identified symptoms.

The machine learning algorithm 1408 may provide insight and outcome yield of the user's behavior in accessing the public information of the A-medical platform as well as the user's private information. The captured information may be sold to pharmaceutical companies, equipment manufacturers, hospitals, governments, insurance, marketers, and other suppliers. As one example, this may be used to develop better medications, medical devices, and healthcare procedures.

Algorithms 1410 can be used to develop special procedures, policies, and smart contracts 1304 to reward a-Medicare subscribers who practice a healthy lifestyle. The cryptographic currency tokens may be awarded to the group of patients or subscribers who have limited use hospitalizations and doctor visits. If desired, the same group of users may share their tokens with patients who are in urgent need of economic support for their surgery, operation, and other medical needs (e.g., family health).

The system is also designed to increase competition among healthcare workers. The competition for health benefits the healthcare industry and providers in providing patient-centric support. Competition has further led to collaboration, partnership and joint research, as well as the development of better pharmaceuticals, medical devices, precision care and other technologies. Competitive products reduce the cost of medication, medical services and other healthcare without affecting quality care.

Through advance agreements with competing entities and/or the use of intelligent contracts 1304, the system publishes information that is shared with competing healthcare actors, can facilitate care, accurate use of medications, verification of peer-to-peer medical journals, and identification and sharing of potential illnesses (e.g., new viruses) and best tools for contact tracking.

a-Medicare, a healthcare platform, will provide leadership by creating alliances and conferences with insurance companies, suppliers, pharmaceutical companies, equipment manufacturers, financial institutions, insurers, governments and assistance organizations to establish policies and standards in the ever-increasing complexity of healthcare practices worldwide.

A-medical's server-based processes and databases are hosted on the cloud Infrastructure as a Service (IaaS). The single database and data warehouse are PostgreSQL based services and block chain based distributed book technology (DLT). These databases securely store HIPAA mandatory PHI and PII data, patient, vendor, diagnosis, research, financial, advertising, insurance and related healthcare data. Thousands of software Web services and other process driven a-medical platforms based on SQL and machine learning algorithms host healthcare data managed by PostgreSQL.

Some implementations of the system include protocols for reusing personal medical devices, excess tokens, and unused medications. Encouraging the reuse of well-conditioned personal medical devices (e.g., walkers, oxygen tanks) for patients in need thereof. Reusing these devices will eliminate unnecessary waste and contribute to environmental and climate change. By sharing these devices, the giver will receive a token award, for example for future doctor visits and hospital care. These tokens are assembled in the user's account with other tokens received from other activities, such as participating in advertisement-based content.

Patients, subscribers and other online users who have excess a-medical tokens are encouraged to voluntarily offer tokens for use by less financially competent or token-deficient patients for necessary procedures and other healthcare needs. The a-Medicare physician may authorize unused and unexpired prescription drugs for patient use, especially during periods of inventory crisis during pandemics. The giver of tokens, unused medications and medical devices will receive additional awards of tokens as happy donors and as a thank you presentation for the patient and a-Medicare.

In some embodiments of the invention, the sharing of medical records helps keep the system up to date and informed by both the user and the caregiver. Medical records, diagnoses, drug use, and the type of care a patient receives can be shared with advertisers, pharmaceutical companies, drug and medical equipment manufacturers by cleansing (scrub) PHI and PII data. The desire to share these types of data will lead to faster cures, the discovery of new drugs, and improvements in healthcare procedures and procedures. Extreme caution is strictly followed to ensure that PHI, PII and diagnostic data are not revealed to unauthorized personnel.

The sharing of healthcare data will also be used to develop a matching algorithm engine to match patients with possible organ donors from around the world. At maturity, hospitals or medical clinics that have the closest organ donors searched in the a-medical federated database have the skills and experience to transfer the organs to legitimate recipients, while taking into account legal, ethical and political sensitivities.

Some embodiments of the invention provide transparency of health insurance claims. The system promotes the transparency of each health insurance claim that a citizen proposes to a nationwide doctor's office, specialist, hospital or medical facility (private or public). In some embodiments, this may include pricing issued by healthcare providers and pharmaceutical companies, but may also include storing medical receipts from user transactions where the individual fees are processed to compile averages that can be broken by countries, states, regions, or hospital/care providers.

FIG. 17 illustrates an early warning system for fraud. With the information collected from the system for transparency of health insurance claims, the fraud early warning system 1500 can be implemented using machine learning algorithms 1502 to counteract improper practices and procedures, thereby preventing fraud through medical checks, unnecessary tests, over-prescribed medications, and over-billing. The early fraud warning system of a-Medicare creates a network of providers (suppliers) 1504, hospital administrators 1506, doctors, insurers, government agencies 1508, and other actors. The system uses the a-medical federation database and other criminal databases to compare with fraudulent transactions that are about to be committed or have been committed. Autonomous machine learning algorithm 1502 detects, triggers, and notifies all relevant actors through autonomous notification system 1510. The autonomous notification system notifies based on the triggering of a high probability situation of impending fraud. The autonomous notification system 1510 communicates bi-directionally with C3M 1512.

The system also compares the patient's symptoms to the patient's treatment and billing, charges, medical procedures, or any identity theft 1514 reported to the a-medical global network 1516, and the machine learning algorithm 1502 identifies unnecessary medications, unexecuted services, unnecessary or expensive billing for the actual performed supply, receive rebates, billing referrals (billing referrals), and disqualified staff. This information is compared to the allowable price range from the a-Medicare federation database and other established billing rates from corporate bills. This information is then used to manually verify and analyze fraudulent transactions for reporting. The system records details of fraudulent transactions and bad actors. Based on the insights and results, the system will trigger notifications from the notification system 1510 to insurers, hospital administrators, and government agencies.

Those of skill in the art will readily appreciate, in light of the present teachings, that any of the foregoing steps and/or system modules may be suitably replaced, reordered, removed, and additional steps and/or system modules may be inserted as desired for a particular application, and that the system of the foregoing embodiments may be implemented using any of a variety of suitable processes and system modules, and is not limited to any particular computer hardware, software, middleware, firmware, microcode, etc.

For any method steps described in this application that may be performed on a computing machine, a typical computer system, when appropriately configured or designed, may be used as the computer system in which those aspects of the invention may be embodied. Such computers referenced and/or described in this disclosure may be any type of computer, general purpose computer, or some special purpose computer such as, but not limited to, a workstation, mainframe, GPU, ASIC, etc. The program may be written in C, Java, Brew, or any other suitable programming language. The program may reside on a storage medium such as magnetic or optical, such as but not limited to a computer hard drive, a removable disk or media, such as but not limited to a memory stick or SD media, or other removable media. The program may also be run on a network, for example, where a server or other machine sends signals to a local machine, which may allow the local machine to perform the operations described herein.

System integration with client/server systems

Fig. 18 is a block diagram depicting an exemplary client/server system that may be used by exemplary web/networked-enabled embodiments of the present invention.

Communication system 1600 includes a number of clients, represented as client 1602 and client 1604, a number of local networks, represented as local network 1606 and local network 1608, a global network 1610, and a number of servers, represented as server 1612 and server 1614.

Client 1602 can communicate bi-directionally with local network 1606 over a communication channel 1616. The client 1604 may communicate bi-directionally with the local network 1608 through a communication channel 1618. The local network 1606 may communicate bi-directionally with the global network 1610 over a communication channel 1620. The local network 1608 may communicate bi-directionally with the global network 1610 over communication channels 1622. The global network 1610 can communicate bi-directionally with the

servers

1612 and 1614 over a communication channel 1624. The server 1612 and the server 1614 can communicate with each other in two-way over a communication channel 1624. Further, the

clients

1602, 1604,

local networks

1606, 1608, the global network 1610, and the

servers

1612, 1614 can each be in bidirectional communication with each other.

In one embodiment, the global network 1610 may operate as the internet. Those skilled in the art will appreciate that communication system 1600 may take many different forms. Non-limiting examples of the form of communication system 1600 include a Local Area Network (LAN), a Wide Area Network (WAN), a wired telephone network, a wireless network, or any other network that supports data communications between various entities.

Clients

1602 and 1604 may take many different forms. Non-limiting examples of

clients

1602 and 1604 include personal computers, Personal Digital Assistants (PDAs), cellular telephones, and smart phones.

Client 1602 includes CPU 1626, pointing device 1628, keyboard 1630, microphone 1632, printer 1634, memory 1636, mass storage 1638, GUI 1640, camera 1642, input/output interface 1644, and network interface 1646.

CPU 1626, pointing device 1628, keyboard 1630, microphone 1632, printer 1634, memory 1636, mass storage 1638, GUI 1640, camera 1642, input/output interface 1644 and network interface 1646 may communicate with each other in a unidirectional manner or in a bidirectional manner over communication channel 1648. The communication channel 1648 may be configured as a single communication channel or multiple communication channels.

CPU 1626 may be comprised of a single processor or multiple processors. CPU 1626 may be of various types, including microcontrollers (e.g., with embedded RAM/ROM) and microprocessors, such as programmable devices (e.g., RISC or SISC based, or CPLD and FPGA), and devices that cannot be programmed, such as gate array ASICs (application specific integrated circuits) or general purpose microprocessors.

Memory 1636 is typically used for transferring data and instructions in a bi-directional manner to CPU 1626 as is well known in the art. As previously mentioned, memory 1636 may include any suitable computer-readable medium intended for data storage, such as those described above, without including any wired or wireless transmission, unless otherwise specified. Mass storage 1638 may also be coupled bi-directionally to CPU 1626 and provide additional data storage capacity and may include any of the computer-readable media described above. The mass storage 1638 may be used to store programs, data and the like and is typically a secondary storage medium such as a hard disk. It will be appreciated that the information retained within mass storage 1638 may, in appropriate cases, be incorporated in standard fashion as part of memory 1636 used as virtual memory.

The CPU 1626 may be coupled to the GUI 1640. The GUI 1640 enables a user to view the operation of the computer operating system and software. CPU 1626 may be coupled to a pointing device 1628. Non-limiting examples of pointing device 1628 include a computer mouse, a trackball, and a touchpad. The pointing device 1628 enables a user to maneuver a computer cursor near a viewing area of the GUI 1640 and select an area or feature in the viewing area of the GUI 1640. CPU 1626 may be coupled to keyboard 1630. Keyboard 1630 enables a user to enter alphanumeric text information into CPU 1626. The CPU 1626 may be coupled to a microphone 1632. The microphone 1632 enables audio generated by the user to be recorded, processed, and transmitted by the CPU 1626. The CPU 1626 may be connected to a printer 1634. The printer 1634 enables a user to print information onto a piece of paper. The CPU 1626 may be connected to a camera 1642. The camera 1642 enables generated video or video captured by the user to be recorded, processed, and transmitted by the CPU 1626.

CPU 1626 may also be coupled to an input/output interface 1644 that connects to one or more input/output devices, such as a CD-ROM, video monitor, trackball, mouse, keyboard, microphone, touch-sensitive display, transducer card reader, magnetic or paper tape reader, tablet computer, stylus, voice or handwriting recognizer, or other well-known input devices, such as other computers, of course.

Finally, CPU 1626 optionally may be coupled to a network interface 1646, network interface 1646 enabling communications with external devices such as a database or a computer or a telecommunications or Internet network using an external connection shown generally as communication channel 1616, communication channel 1616 may be implemented as a hardwired or wireless communication link using suitable conventional techniques. Over such a connection, CPU 1626 may receive information from the network, or may output information to the network in the course of performing the method steps described in the teachings of the present invention.

System integration with Web-enabled and/or networked devices

Fig. 19 illustrates a block diagram depicting a conventional client/server communication system, which may be used by exemplary network/networking-enabled embodiments of the present invention.

Communication system 1700 includes a plurality of networked areas (network areas), illustrated as network area 1702 and network area 1704, a global network 1706, and a plurality of servers, illustrated as server device 1708 and server device 1710.

Network region 1702 and network region 1704 may operate to represent networks contained within a geographic area or region. Non-limiting examples of representations of geographic regions of a network region may include zip codes, area codes, states, counties, cities, and countries. Elements within

network regions

1702 and 1704 may operate to communicate with elements within other networking regions, external elements or elements contained within the same network region.

In some implementations, the global network 1706 may operate as the internet. Those skilled in the art will appreciate that communication system 1700 may take many different forms. Non-limiting examples of the form of communication system 1700 include a Local Area Network (LAN), a Wide Area Network (WAN), a wired telephone network, a cellular telephone network, or any other network that supports data communications between various entities via a hardwired or wireless communication network. The global network 1706 may operate to communicate information between various networked elements.

Server devices

1708 and 1710 may be operable to execute software instructions, store information, support database operations, and communicate with other networked elements. Non-limiting examples of software and scripting languages that may be executed on server device 1708 and server device 1710 include C, C + +, C #, and Java.

The network region 1702 is operable to communicate bi-directionally with the global network 1706 over a communication channel 1712. The network area 1704 is operable to bi-directionally communicate with the global network 1706 via communication channels 1714. The server apparatus 1708 is operable to bi-directionally communicate with the global network 1706 via a communication channel 1716. The server apparatus 1710 is operable to bi-directionally communicate with the global network 1706 via a communication channel 1718.

Network regions

1702 and 1704, global network 1706, and

server devices

1708 and 1710 are operable to communicate with each other and with each other networked device located within communication system 1700.

The server device 1708 includes a network device 1720 and a server 1722. The network device 1720 may be operable to communicate bi-directionally with the global network 1706 over a communication channel 1716 and with the servers 1722 over a communication channel 1724. Server 1722 is operable to execute software instructions and store information.

Network region 1702 includes a plurality of clients, examples of which are represented as client 1726 and client 1728. Client 1726 includes network device 1734, processor 1736, GUI 1738, and interface device 1740. Non-limiting examples of devices of GUI 1738 include monitors, televisions, cellular phones, smart phones, and PDAs (personal digital assistants). Non-limiting examples of interface devices 1740 include a pointing device, mouse, trackball, scanner, and printer. The network device 1734 may communicate bi-directionally with the global network 1706 over communication channel 1712 and with the processor 1736 over communication channel 1742. GUI 1738 may receive information from processor 1736 over communication channel 1744 for presentation to a user for viewing. Interface device 1740 is operable to transmit control information to and receive information from processor 1736 over a communication channel 1746. Network area 1704 includes multiple clients, sample of which are represented as client 1730 and client 1732. Client 1730 includes network device 1748, processor 1750, GUI 1752, and interface device 1754. Non-limiting examples of devices of GUI 1752 include monitors, televisions, cellular phones, smart phones, and PDAs (personal digital assistants). Non-limiting examples of interface devices 1754 include pointing devices, mice, trackballs, scanners, and printers. Network device 1748 may communicate bi-directionally with global network 1706 over communication channel 1714 and with processor 1750 over communication channel 1756. GUI 1752 may receive information from processor 1750 over communication channel 1758 to present to a user for viewing. Interface device 1754 may be operative to send control information to processor 1750 and receive information from processor 1750 via communication channel 1760.

For example, consider a case where a user interacting with client 1726 may want to execute a networked application. The user may enter an IP (internet protocol) address for a networked application using the interface device 1740. The IP address information may be communicated to processor 1736 over a communication channel 1746. Processor 1736 may then transmit the IP address information to network device 1734 via communication channel 1742. The network device 1734 may then transmit the IP address information to the global network 1706 over the communication channel 1712. The global network 1706 may then transmit the IP address information to the network device 1720 of the server device 1708 over the communication channel 1716. The network device 1720 may then transmit the IP address information to the server 1722 over the communication channel 1724. The server 1722 may receive the IP address information and, after processing the IP address information, may transmit the return information to the network device 1720 via the communication channel 1724. The network device 1720 may transmit the return information to the global network 1706 via a communication channel 1716. The global network 1706 may transmit the return information to the network device 1734 over the communication channel 1712. Network device 1734 may transmit return information to processor 1736 over communication channel 1742. Processor 1736 may transmit the return information to GUI 1738 via communication channel 1744. The user may then view the return information on GUI 1738.

Having described the above infrastructure and components, exemplary embodiments of the present invention provide a method for a unified platform for general healthcare and related services. FIG. 20 sets forth a flow chart illustrating an exemplary method for a unified platform for general healthcare and related services according to embodiments of the present invention. Referring to the present embodiment, the method begins at start operation 1800. Providing a blockchain-based software program stored in a non-transitory computer-readable storage digital medium and executed by one or more processors of a computer-based system is accomplished in operation 1802. Upon providing the blockchain-based software program in operation 1802, the method continues by providing a graphical user interface coupled to the non-transitory computer-readable storage digital medium and the processor in operation 1804. Using computer advertisement-based provisioning module hardware, the advertising content is populated onto a screen of the graphical user interface based at least in part on the participant completing a successful consumption of the advertising content indicated by the survey and returning it to the private advertiser, wherein the participant earned credit points in return for consumption of the advertising content, which is included in operation 1806. The following is accomplished in operation 1808: the participants are rewarded credit points for their healthcare bills or premiums using computer advertisement based provisioning module hardware. Coordinating where the organs of the organ donor are to be donated is accomplished in operation 1810 based on the matching step, the medical records of the participants, and the organ donor information. Completed in operation 1812: the transportation of the donated organ is tracked based on the facilitation step and the stored participant medical record. The tracking step 1812 includes tracking the organ extraction location and delivery of the organ to the destination. Completed in operation 1814: a recycling program is created for the unused medication, including the step of rewarding the participant credit points, thereby incentivizing the participant to recycle the unused medication to a local pharmacy. Assigning credit points is accomplished in operation 1816, wherein the assigned credit points include at least one of credit points earned by participation in viewing the advertising content and credit points earned from participation in the recycling program, wherein at least a portion of the credit points are assigned to a plurality of entities including the user, the medical insurer, the pharmacy, and the government health agency, wherein the portion of the user's credit points are recorded in a virtual bank of credit points for selective use on medical bills and services.

In some embodiments, blockchain-based program 1802 includes an open distributed book configured to record transactions between organ donors and participants, including organ donors and participants, in a verifiable and perpetuable manner.

In some embodiments, the blockchain-based program 1802 shown in fig. 20 is further configured to perform the steps of processing and prioritizing health insurance claims in at least one of a nationwide public or private doctor's office, a public or private specialist, and a public or private hospital or medical facility.

In some embodiments, the advertising content 1806 shown in FIG. 20 also includes a digital platform for advertising where private advertisers pay to promote their products to a specific target audience using surveys at the end of each advertisement.

Fig. 21 illustrates a flowchart of a subroutine of the blockchain based software program of operation 1802 shown in fig. 20, and is configured to perform operation 1902: storing the participant's personal electronic medical records in a healthcare database as a growing list of personal electronic medical records, including blocks of personal electronic medical records cryptographically linked together, wherein each block of personal electronic medical records contains a cryptographic hash of a previous block of personal electronic medical records. Once a personal electronic medical record is recorded, the personal electronic medical record in any given block cannot be retroactively changed without changing all subsequent blocks of personal electronic medical records, which require most of the network's consent. After operation 1902, operation 1904 is completed: the organ donor information is stored in the healthcare database as a growing list of organ donor information, comprising pieces of organ donor information cryptographically linked together, wherein each piece of organ donor information contains a cryptographic hash of a previous piece of organ donor information. Once the organ donor information is recorded, the organ donor information in any given chunk cannot be retroactively changed without changing all subsequent organ donor information chunks, which require substantial network consent. In operation 1906, the following is completed: an international universal database is created, wherein the international universal database is configured to at least connector donors and recipients nationwide or worldwide. In operation 1908, the following is completed: the donated organ is matched to the participant according to the participant's stored electronic medical record and organ donor information. In operation 1910, the following is completed: the location where the organ is to be donated is determined based on the matching step. Completed in operation 1912 are: a variable-based panel system is provided, including a graphical user interface, on which a user can manage at least one of doctor appointments, electronic medical records, medical insurance, hospital visits, medications, and pharmacies, wherein the variable-based panel is configured to be locked with an assigned ID and social security number.

FIG. 22 illustrates a flowchart of a subroutine of operation 1804 in FIG. 20. The graphical user interface displays on a screen a graphical output of the computer-based system, comprising: displaying on a screen an interaction portal defined by a graphical button represented by an interaction location, as shown in operation 2002; and displaying graphical buttons represented by the interaction locations, as shown in operation 2004, wherein when engaged, the interaction buttons perform at least one function 2006, including providing a menu 2020 of executable sub-functions, including displaying a credit points bank 2008, presenting an advertisement 2010, displaying healthcare information 2012, whereby selection of each option executes a command to query the server 2014, receive real-time information 2016, and populate information 2018 on the screen.

Fig. 25, 26, and 27 illustrate visual displays associated with some exemplary operations discussed in the flowchart of fig. 24. In the exemplary embodiment shown in FIG. 25, the user is provided with an interactive portal login module 2202 on a graphical user interface 2200. After authenticating the user and logging the user in, the graphical user interface 2200 will display a user portal 2204 with several buttons 2208 representing interaction locations 2206, as shown in fig. 26, which upon clicking will execute a sub-routine, such as taking the user to a specific sub-page. Fig. 27 illustrates the patient management portion of a patient portal sub-page 2210 on a graphical user interface 2200, which allows a user to enter new information. Other sub-pages may be executed from other buttons in the user portal 2204. The user portal allows a user to monitor and view all relevant information about the user or the user's patients' healthcare information in a unified area. This may also include ad-based credit offering, billing functions and monitoring, etc., all integrated in one location, although the information may be taken from multiple sources, these areas will be discussed further with reference to fig. 28. Information taken from other sources may be converted into an integrable generic template 2212, such as that shown in FIG. 27. While fig. 27 includes a fillable template from the user, it should also be understood that the system also receives information from non-interactive templates, which are then processed by the system, and the information therein is read and uploaded to the patient's portal without direct action by the patient.

As a furtherance and combination of the above system, the GUI combines features that allow generic portal access by modules and integrated programs that include tracking information related to drug and organ donations, health information, generic templates for users to enter and display data in a generic format, and for users to view content including advertisements and credit balances obtained from viewing advertisements.

FIG. 28 illustrates an exemplary embodiment of graphical user interface 2220 in which there are multiple modules, each representing a sub-routine and displaying the interaction location of each region, e.g., a clickable button. For example, these modules may include an advertising module 2214, an organ tracking module 2216, a recommended health plan module 2218, a credit balance module 2220, a medical records module 2222, an integration module 2224 for interacting with the user's personal or voice assistant, an image upload and processing module 2226, a medical billing module 2228, and a healthcare provider information module 2230. It should be appreciated that each of these modules displays data received from multiple sources in real time for user interaction, and is interactive, when clicked, taking the user to a sub-screen of GUI 2220, as shown in fig. 27.

The present invention is a practical application of the software integration principle, as it combines different features into a single portal, where they can interact and interact. For example, if organ donations cannot be made before a pre-specified threshold, the treatment plan may be automatically updated. Furthermore, the exemplary embodiments provide a technical solution to the technical problem, wherein the problem stems from the separate and/or fragmented provision of healthcare "related" applications. While there are healthcare systems to meet medical needs, the present invention allows for patient-centric solutions that include content beyond healthcare-specific information, such as advertising-sponsored credit points, allowing users to integrate funds into medical bills, etc., but which do not themselves (referred to as credit points) belong to healthcare products. Furthermore, it should be appreciated from the above-mentioned solutions that these solutions cannot be done in the mind of the user, as they require variable input from multiple sources that interact with variable real-time data from other sources to obtain real-time output that is affected by a large number of data inputs at the same time.

The system is applicable to all levels of users, each of which may receive a different composition of graphical user interface 2200. For example, the patient may receive a layout as shown and described above in fig. 28. However, the healthcare professional may receive a portal with areas to upload notes, scan notes into a digital text format, upload images, run machine learning functions to analyze images and notes to reduce the time spent diagnostically or providing instant second opinions, manually upload organ information donation availability and/or tracking information if not controlled by an artificial intelligence management system, send safety messages to the patient, and/or upload and/or modify billing areas. Also, advertisers may receive simpler portals, where the only feature may be to upload advertising media and filter the user's targeted features to receive the media.

Since multiple individuals may affect a single user portal, the system accepts the input and converts it to a universal data format, including the universally implemented metadata read by the end user's portal program, and will provide real-time information that quickly adapts to the new information received, thereby modifying the displayed information, including recommendations, credit balances, and healthcare information. In addition, because the system includes artificial intelligence assisted machine learning algorithms, the system may be continually monitored and updated, providing information beyond user input, where such additional information is neither uploaded by, nor recommended by, the physical user.

In some embodiments, blockchain based program 1802 is further configured to perform the steps of: virtual personal health assistance ("VPHA", virtual personal health assistant) is provided, wherein the virtual personal health assistance is configured to be operable to listen to voice and/or text commands 1108 to provide information and assistance, as understood in the flow chart shown in fig. 23.

In some embodiments, further as shown in fig. 23, the virtual personal health assistance is a home-based robot 1002 connected to the blockchain-based program 1802 through a home portal 1104, and the robot 1002 includes a memory, the robot 1002 including instructions on the memory for receiving voice commands 1116, and performing functions 1108 based on the commands, and bi-directionally communicating 1118 with the internet-of-things device 220, the internet-of-things device 220 including at least one of a smart wearable device and a chip embedded in the skin of the user.

FIG. 24 illustrates additional steps of an exemplary method for a unified platform for general healthcare and related services according to the embodiment illustrated in FIG. 20. In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to an embodiment of the present invention illustrated in fig. 20 further comprises operation 2102: sending an automatic variable-based notification pushed to a user portal displayed on a screen of a graphical user interface, wherein the notification results from at least real-time changes in patient information, including changes in status of audit reports by machine learning, status observed by wearable and internet of things technologies, availability of organs, and diagnosis.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to an embodiment of the present invention illustrated in fig. 20 further includes an operation 2104: raw data input is converted to a universally readable format on a server and graphical user interface components of the system to facilitate faster searching and automatic comparison of data through a machine learning interface of the system, whereby raw data is converted to the universally readable format as it is input to the system while the data is in the server and at the output of the system. The generic readable format may be configured to be easily attached to a blockchain to facilitate faster transfer of data, whereby the generic readable format includes executable functions to compress and decompress raw data, wherein the blockchain will not contain raw data or imagery. The generic readable format may exist as compressed metadata that is decoded by the graphical user interface for a particular variable-based dashboard system and display portal.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to the embodiment of the present invention illustrated in fig. 20 further includes operation 2106: the recommended treatment and medication for the patient is adjusted based on the availability of the organ.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to an embodiment of the present invention illustrated in fig. 20 further includes operation 2108: scheduling appointments with healthcare practitioners.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to the embodiment of the present invention illustrated in fig. 20 further includes operation 2110 of: the purchase of the medication is facilitated based on the participant's medical records.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to an embodiment of the present invention illustrated in fig. 20 further includes operation 2112: drug and organ transport was tracked based on participant medical records. Operation 2112 of tracking includes tracking the organ extraction location and delivery of the organ to the target location.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to an embodiment of the present invention illustrated in fig. 20 further includes operation 2114: the healthcare-related cost information is made public by displaying the healthcare-related cost information in a panel of a portal displayed on a graphical user interface, thereby creating competition within the healthcare industry.

In some embodiments, the exemplary method for a unified platform for general healthcare and related services according to an embodiment of the present invention illustrated in fig. 20 further includes operation 2116: defining symptoms and genetic characteristics of the participant by implementing machine learning, wherein the machine learning system receives input from the end user and stores the input in a memory of a healthcare computing module that receives and processes the input of the end user to further generate and transmit suggested care options to the end user at a results module, wherein the machine learning system is configured to compare the medical record to the medical record of the participant using the medical record, wherein the medical record includes medical data of the patient, medical images, and stored medical information including medical images of non-patients to generate a medical diagnosis based on the defined symptoms and genetic characteristics of the participant, wherein the medical diagnosis is configured to be based at least in part on the transformed medical record of the blockchain based software program. Operation 2116 of defining the participant's symptoms and genetic characteristics by performing machine learning further includes identifying, pixel by pixel, lights and colors that are undetectable to the naked eye, classifying the identifications and comparing at least one identification to at least one medical image to detect abnormalities, and differences, and automatically applying summary text containing written diagnoses for reading by the user.

In some embodiments, the method as shown in fig. 20-24 is implemented using a non-transitory computer readable storage medium having stored thereon an executable program, where the program instructs one or more processors to perform the following steps of the method.

In some embodiments, the method as shown in fig. 20 is introduced into a computing system having at least one processor, a graphical user interface, and at least one storage device including instructions embodied thereon, wherein the instructions, when executed by the one or more processors, cause the processors to perform operations for processing data in a medical assessment workflow, wherein the operations include steps according to the method.

It will be further apparent to those skilled in the art that at least a portion of the novel method steps and/or system components of the present invention may be implemented and/or located at a location that may be beyond the jurisdiction of the United States of America (USA), whereby it will be readily appreciated that at least a subset of the novel method steps and/or system components in the foregoing embodiments must be implemented within the jurisdiction of the united states, for the benefit of the entities therein or to achieve the objectives of the present invention. Accordingly, some alternative embodiments of the present invention may be configured to include a smaller subset of the aforementioned means and/or steps, which the application designer will selectively decide based on the actual considerations of a particular implementation to implement and/or locate within the jurisdiction of the United states.

For example, any of the above-described method steps and/or system components (e.g., without limitation, remote servers) that may be remotely executed over a network may be executed and/or located outside of the jurisdiction of the united states, while the remaining method steps and/or system components (e.g., without limitation, local clients) of the foregoing embodiments typically need to be located/executed in the united states for practical considerations. In a client-server architecture, a remotely located server typically generates and transmits the required information to a U.S. based client for use in accordance with the teachings of the present invention. Those skilled in the art will readily appreciate from the teachings of the present invention which aspects of the invention may or should be located locally and which may or should be located remotely, depending on the needs of a particular application. Accordingly, for any claim structure defined below in accordance with 35 USC § 112(6)/(f), it is contemplated that corresponding means and/or steps for performing the claimed functions are implemented locally within the jurisdiction of the united states, whereas other aspects of performing or being remotely located outside the united states are not intended to be interpreted in accordance with 35 USC § 112(6) pre-AIA or 35 USC § 112(f) post AIA. In some embodiments, methods and/or system components that may be remotely located and/or performed include, but are not limited to: any one or more of the operations described in connection with the systems and/or processes of the "a-medical" system and/or the digital platform.

It is important to note that under the united states law, all the claims must be set forth as a coherent, cooperative set of limitations that work in combination to achieve useful results as a whole. Thus, for any claim having a functional limitation that is interpreted according to 35 USC § 112(6)/(f), wherein the discussed embodiments are implemented as a client-server system having a remote server located outside the united states, each such recited function is intended to refer to a function that logically combines the information limited by that claim with at least one other limitation of the claim.

For example, in a client-server system where certain information stated according to 35 USC § 112(6)/(f) is dependent on one or more remote servers located outside the united states, it is intended that each such recited function under 35 USC § 112(6)/(f) will be interpreted as a function of the local system receiving remotely generated information required by locally enforced entitlement restrictions, wherein the structure and/or steps enabling and engendering said function stated under 35 USC § 112(6)/(f) are corresponding steps and/or means located within the jurisdiction of the united states, receiving and providing this information to clients (such as, but not limited to, client processing and transmission networks in the united states). When the application is filed or patented in a jurisdiction other than the united states, "united states" in the above description should be replaced with the relevant country or countries or legal organizations having the jurisdiction in which patent infringement may be performed for the application, and "35 USC § 112 (6)/(f)" should be replaced with the closest corresponding regulation in the patent laws of the relevant country or countries or legal organizations.

All the features disclosed in this specification (including any accompanying abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.

It should be noted that, according to U.S. law 35 USC § 112(1), all claims must be supported by sufficient disclosure in this patent specification and that any material known to those skilled in the art need not be explicitly disclosed. However, 35 USC § 112(6) requires that structures corresponding to the functional limitations explained according to 35 USC § 112(6) must be explicitly disclosed in the patent specification. Furthermore, the USPTO's vetting policy to initially process and retrieve prior art under the maximum interpretation of the "means for" or "step" claim restrictions means that the broadest preliminary retrieval of the 35 USC 112(6) (post AIA 112(f)) functional restrictions must be conducted to support legally valid vetting of the USPTO's policy for maximum interpretation of "means for". Accordingly, the USPTO will find a wealth of prior art documents, including disclosure of particular structures and elements, which are suitable as corresponding structures to meet all of the functional limitations in the claims below, as interpreted in accordance with 35 USC § 112(6) (post AIA 112(f)) when such corresponding structures are not expressly disclosed in the foregoing patent specification.

Accordingly, for any inventive element/structure corresponding to functional claim limitations that are not expressly disclosed in the aforementioned patent specification, but do exist in patent and/or non-patent documents found during USPTO retrieval, in the following claims construed in accordance with 35 USC § 112(6) (post AIA 112(f)), applicants incorporate herein by reference all such functionally corresponding structures and associated enabling materials for the purpose of providing an explicit structure for achieving the claimed functional means.

Applicants claim that the fact discoverer during any claim building procedure and/or patent allowability review, correctly identifies and incorporates only the portions of each of these documents found during the 35 USC § 112(6) (post AIA 112(f)) limited maximum interpretation search, which is present in at least one patent and/or non-patent document found during the USPTO normal search and/or provided to the USPTO during prosecution.

Applicants also incorporate bibliographic citations by reference to identify all such documents including functionally corresponding structures and associated enabling materials listed in any PTO table-892 or any similar Information Disclosure Statement (IDS) entered into the present patent application by the united states patent and trademark office or the applicant or any third party. Applicants also reserve the right to later modify the present application to explicitly include a reference to such documents and/or to explicitly include structure corresponding to the functionality incorporated by reference above.

Accordingly, for any inventive element/structure in the claims construed below according to 35 USC 112(6) (post AIA 112(f)) that corresponds to a functional claim limitation and that is not explicitly disclosed in the foregoing patent specification, applicants have explicitly stated which documents and materials include otherwise lacking disclosure, and have explicitly stated which portions of such patent and/or non-patent documents should be incorporated by such reference in order to satisfy the disclosure requirements of 35 USC 112 (6). Applicants note that all of the above-identified documents incorporated by reference to satisfy 35 USC § 112(6) must have a filing and/or publication date before the filing and/or publication date of the present application, and are therefore valid prior documents incorporated by reference herein.

Having fully described at least one embodiment of this invention, other equivalent or alternative methods of implementing an integrated digital-based healthcare service procurement and delivery solution according to the invention will be apparent to those skilled in the art. Various aspects of the present invention have been described above by way of illustration, and the specific embodiments disclosed are not intended to limit the invention to the particular forms disclosed. The specific implementation of the integrated digital-based healthcare service procurement and delivery solution may vary depending on the particular environment or application. By way of example and not limitation, the integrated digital-based healthcare service procurement and delivery solution described above is primarily directed to practices related to consumer healthcare; however, similar techniques may alternatively be applied to businesses and/or other private and/or non-private entities, and such implementations of the invention are considered to be within the scope of the invention. Accordingly, the invention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the appended claims. It should also be understood that not all embodiments disclosed in the foregoing specification necessarily satisfy or achieve each object, advantage, or improvement described in the foregoing specification.

Claim elements and steps herein may have been numbered and/or labeled with letters as merely an aid for readability and understanding. Any such numbering and lettering is not intended nor should it be taken to indicate the order of elements and/or steps in the claims as such.

The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed.

The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

The abstract is provided to comply with 37 c.f.r.section 1.72(b), which requires an abstract to allow the reader to ascertain the nature and gist of the technical disclosure. That is, the abstract is provided to introduce a selection of concepts, not to identify any key or essential features of the claimed subject matter. It is submitted with the understanding that it will not be used to limit or interpret the scope or meaning of the claims.

The following claims are hereby incorporated into the detailed description, with each claim standing on its own as a separate embodiment.

Only those claims that use the wording "means for … …" ("means for") or "step for … …" are interpreted in accordance with 35 USC 112, sixth diagraph (pre-AIA) or 35 USC 112(f) post-AIA. In addition, no limitation on the specification is to be read into any claim unless such limitation is explicitly included in the claim.

Claims

1. A method, comprising the steps of:

providing a blockchain based software program stored in a non-transitory computer readable storage digital medium and executed by one or more processors of a computer based system, wherein the blockchain based software program is configured to perform the steps of:

storing the participant's personal electronic medical records in a healthcare database as a growing list of the personal electronic medical records, including blocks of personal electronic medical records cryptographically linked together, wherein each block of personal electronic medical records contains a cryptographic hash of a previous block of personal electronic medical records;

wherein once the personal electronic medical record is recorded, the personal electronic medical record in any given chunk cannot be retroactively modified without modifying all subsequent blocks of personal electronic medical records that require a majority of network consent;

storing organ donor information in the healthcare database as a growing list of the organ donor information, including blocks of organ donor information cryptographically linked together, wherein each block of organ donor information contains an encrypted hash of a previous block of organ donor information;

wherein once the organ donor information is recorded, the organ donor information in any given chunk cannot be used to alter all subsequent organ donations

The organ donor information blocks are retroactively changed under the condition of the organ donor information blocks, and the change of all subsequent organ donor information blocks needs most network consent;

creating an international universal database, wherein the international universal database is configured to connect organ donors and recipients at least nationwide or worldwide;

matching the donated organ with the participant according to the participant's stored electronic medical record and the organ donor information;

determining a location where the organ is to be donated based on the matching step; and

providing a variable-based panel system including a graphical user interface on which a user can manage at least one of doctor appointments, the electronic medical records, medical insurance, hospital visits, medications, and pharmacies, wherein the variable-based panel system is configured to communicate with an assigned ID and social security number

Locking;

providing a graphical user interface coupled to the non-transitory computer-readable storage digital medium and the processor, whereby the graphical user interface displays a graphical output of the computer-based system on a screen, comprising:

displaying on the screen an interaction defined by a graphical button represented by an interaction location

A portal;

displaying the graphical buttons represented by the interactive position, wherein when engaged, the interactive buttons perform at least one function, including providing a menu of executable sub-functions, including displaying credit-points banks, presenting advertisements, displaying healthcare information, whereby selection of each option executes a command to query a server, receive real-time information, and populate the information on the screen;

populating advertising content on the screen of the graphical user interface using computer advertisement-based provisioning module hardware based at least in part on the participant completing successful consumption of the advertising content indicated by the survey and returning it to the private party advertiser, wherein the participant earns credit points in return from consumption of the advertising content;

rewarding credit points of participants for participants' healthcare bills or premiums using the computer advertisement based provisioning module hardware;

coordinating where organs of the organ donor will be donated based on the matching step, participant's medical records and organ donor information;

tracking the transport of the donated organ according to the facilitating step and the stored medical records of the participant;

wherein the tracking step comprises tracking the organ extraction location and delivery of the organ to the target location; creating a recycling program for the unused medication, including the step of rewarding the participants credit points, thereby incentivizing the participants to recycle the unused medication to the local pharmacy; and

assigning credit points, wherein the assigned credit points comprise at least one of the credit points earned by participation in viewing advertising content and the credit points earned from participation in the recycling program, wherein at least a portion of the credit points are assigned to a plurality of entities including the user, the medical insurer, the pharmacy and the government health agency, wherein the portion of the user's credit points are recorded in a virtual bank of credit points for selective use on medical billing and services.

2. The method of claim 1, wherein said blockchain-based software program comprises an open distributed book configured to record transactions between said organ donors and participants, including said organ donors and participants, in a verifiable and perpetuable manner.

3. The method of claim 1, further comprising:

sending an automatic variable-based notification pushed to a user portal displayed on a screen of a graphical user interface, wherein the notification results from at least real-time changes in patient information, including changes in status of audit reports by machine learning, status observed by wearable and internet of things technologies, availability of organs, and diagnostics.

4. The method of claim 1, further comprising:

converting raw data input into a universally readable format on a server and graphical user interface components of a system to facilitate faster searching and automatic comparison of data through a machine learning interface of the system, whereby raw data is converted into the universally readable format as it is input into the system while data is in the server and at the output of the system;

the generic readable format is configured to be readily attached to a blockchain that will not contain raw data or imagery, thereby facilitating faster transmission of the data, whereby the generic readable format includes executable functions to compress and decompress the raw data; and

the generic readable format exists as compressed metadata that is decoded by the graphical user interface for a particular variable-based dashboard system and display portal.

5.A non-transitory computer readable storage medium having an executable program stored thereon, the program instructing one or more processors to perform the steps of:

storing a blockchain based software program in a non-transitory digital storage medium and executed by one or more processors of a computer based system, wherein the blockchain based software program is configured to perform the steps of:

storing organ donor information in the healthcare database as a growing list of organ donor information, including blocks of organ donor information cryptographically linked together, wherein each block of organ donor information contains an encrypted hash of a previous block of organ donor information;

wherein, once the organ donor information is recorded, the organ donor information in any given block cannot be used to alter all subsequent organ donors

scheduling appointments with healthcare practitioners;

matching the donated organ with the participant according to the participant's stored electronic medical record and the organ donor information; and

determining a location where the organ will be donated based on the matching step;

A portal;

displaying the graphical button represented by the interactive position, wherein when engaged, the interactive button performs at least one function, including providing a menu of executable sub-functions, including displaying credit-points banks, presenting advertisements, displaying healthcare information, whereby selection of each option executes a command to query a server, receive real-time information, and populate the information on the screen;

providing an advertising platform configured to be operable to generate credit points for participants viewing advertising content on a graphical user interface, wherein the participants earn the generated credit points in return for viewing advertising content indicated by the participants completing a survey;

coordinating where organs of the organ donor will be donated based on the stored medical records and organ donor information;

adjusting the recommended treatment and medication for the patient based on the availability of the organ;

facilitating purchase of the medication according to the participant's medical record;

tracking the transport of drugs and organs according to the participant's medical records, the tracking step including tracking organ extraction locations and organ delivery to target locations;

creating a recycling program for the unused medication, including the step of rewarding the participant credit points, thereby incentivizing the participant to recycle the unused medication to a local pharmacy; and

6. The program for instructing one or more processors of claim 5, further comprising:

sending an automatic variable-based notification pushed to a user portal displayed on a screen of a graphical user interface, wherein the notification results from at least real-time changes in patient information, including changes in status of audit reports by machine learning, status observed by wearable and internet of things technologies, availability of organs, and diagnosis.

7. The program for indicating one or more processors of claim 5, further comprising:

converting raw data input into a universally readable format on a server and graphical user interface components of a system to facilitate faster searching and automatic comparison of data through a machine learning interface of the system, whereby raw data is converted into the universally readable format upon input to the system while data is in the server and upon output of the system;

8. The program for indicating one or more processors of claim 5, further comprising the steps of:

the healthcare-related cost information is made public by displaying the healthcare-related cost information in a panel of the portal displayed on the graphical user interface, thereby creating competition within the healthcare industry.

9. A computing system, comprising:

at least one or more processors;

a graphical user interface; and

at least one storage device comprising instructions embodied thereon, wherein the instructions, when executed by the one or more processors, cause the processors to perform operations for processing data in a medical assessment workflow, wherein the operations comprise:

providing a blockchain based software program stored in a non-transitory digital storage medium and executed by the one or more processors, wherein the blockchain based software program is configured to perform the steps of:

matching the donated organ with the participant according to the participant's stored medical records and organ donor information; and

scheduling appointments with medical practitioners according to the matching steps;

providing a graphical user interface software program stored in a non-transitory digital storage medium and executed by the one or more processors whereby the graphical user interface displays a graphical output of the graphical user interface software program on a screen, comprising:

displaying on the screen an interaction portal defined by graphical buttons represented by interaction locations;

providing an advertising platform configured to be operable to generate credit points for participants viewing advertising content on the graphical user interface, wherein participants earn credit points for viewing the advertising content as indicated by the participants completing a survey;

coordinating where organs of the organ donor will be donated based on the matching step and stored medical records of participants;

facilitating purchase of the participant's medication based at least in part on the participant's medical record;

tracking the transport of the medication according to the facilitating step and the participant's medical record;

tracking the transport of the donated organ according to the coordination step and the participant's medical record;

creating a recycling program for the unused medication, including the step of rewarding the participant credit points, thereby incentivizing the participant to recycle the unused medication to a local pharmacy;

rewarding the participants for credit points for the participants' healthcare bills or premiums using the computer advertisement-based provisioning module hardware; and

10. The computing system of claim 9, further comprising:

11. The computing system of claim 9, further comprising:

12. A non-transitory computer readable storage medium having an executable program stored thereon, the program instructing one or more processors to perform steps comprising:

Retroactively modified in the case of the organ information block, the modification of all subsequent organ donor information blocks requiring the majority of network consent;

scheduling appointments with medical practitioners;

A portal;

providing an advertising platform configured to be operable to generate credit points for participants viewing advertising content, wherein the participants earn the generated credit points in return for viewing advertising content indicated by the participants completing a survey on a graphical user interface;

adjusting recommended treatments and medications for the patient based on the availability of the organ;

facilitating the purchase of the medication according to the participant's medical record;

assigning credit points, wherein the assigned credit points include at least one of the credit points earned by participation in viewing advertising content and the credit points earned from participation in the recycling program, wherein at least a portion of the credit points are assigned to a plurality of entities selected from the group consisting of users, medicare, pharmacy, and government health agencies, wherein portions of the user's credit points are recorded in a virtual bank of credit points for selective use on medical bills and services;

defining symptoms and genetic characteristics of the participant by implementing machine learning, wherein the machine learning system receives input from the end user and stores the input in a memory of the healthcare computing module, the healthcare calculation module receives and processes the end-user's input to further generate and transmit suggested care options to the end-user at a results module, wherein the machine learning system is configured to compare the medical record to a medical record of a participant using the medical record, wherein the medical record includes medical data of the patient, medical images, and stored medical information including medical images of non-patients, thereby generating a medical diagnosis based on the defined symptoms and genetic characteristics of the participants, wherein the medical diagnosis is configured to be based at least in part on the converted medical record of the blockchain-based software program; and

the defining of the participant's symptoms and genetic characteristics by implementing machine learning further includes identifying, pixel by pixel, gross and color undetectable by the naked eye, classifying the identifications and comparing at least one identification to at least one medical image to detect abnormalities, abnormalities and differences, and automatically applying summary text containing written diagnoses for reading by a user.