AU2021104781A4 - A 5g network-based system and method for intelligent health-care applications using machine learning approach - Google Patents
A 5g network-based system and method for intelligent health-care applications using machine learning approach Download PDFInfo
- Publication number
- AU2021104781A4 AU2021104781A4 AU2021104781A AU2021104781A AU2021104781A4 AU 2021104781 A4 AU2021104781 A4 AU 2021104781A4 AU 2021104781 A AU2021104781 A AU 2021104781A AU 2021104781 A AU2021104781 A AU 2021104781A AU 2021104781 A4 AU2021104781 A4 AU 2021104781A4
- Authority
- AU
- Australia
- Prior art keywords
- patient
- health
- disease
- new person
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
- 238000010801 machine learning Methods 0.000 title claims abstract description 18
- 238000013459 approach Methods 0.000 title claims abstract description 14
- 238000000034 method Methods 0.000 title claims description 26
- 230000036541 health Effects 0.000 claims abstract description 49
- 201000010099 disease Diseases 0.000 claims abstract description 45
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims abstract description 45
- 238000012806 monitoring device Methods 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims abstract description 8
- 230000008569 process Effects 0.000 claims description 6
- 230000036772 blood pressure Effects 0.000 claims description 3
- 238000011156 evaluation Methods 0.000 claims description 3
- 230000001537 neural effect Effects 0.000 claims description 3
- 230000008901 benefit Effects 0.000 description 9
- 238000004891 communication Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 208000031888 Mycoses Diseases 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 206010017533 Fungal infection Diseases 0.000 description 1
- 206010037660 Pyrexia Diseases 0.000 description 1
- 208000036142 Viral infection Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000009385 viral infection Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
- A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
- A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
- A61B5/7282—Event detection, e.g. detecting unique waveforms indicative of a medical condition
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/48—Diagnostic techniques
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Pathology (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Biophysics (AREA)
- Heart & Thoracic Surgery (AREA)
- Veterinary Medicine (AREA)
- Physiology (AREA)
- Artificial Intelligence (AREA)
- Cardiology (AREA)
- Psychiatry (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Optics & Photonics (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Evolutionary Computation (AREA)
- High Energy & Nuclear Physics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Mathematical Physics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Fuzzy Systems (AREA)
- Emergency Medicine (AREA)
- Psychology (AREA)
- Vascular Medicine (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The present invention generally relates toa5G network-based
system for intelligent health-care applications comprises a database
wirelessly connected with a plurality of health monitoring devices and
server of various hospitals through a 5G network for receiving a set of
health parameters along with disease types and physical records of
patients; a central processing unit in configuration with a machine
learning approach for categorizing thereby interpreting data of patients
stored in the database; a control unit for receiving health report of a new
person/patient thereby evaluating real time health of the new
person/patient in a regular interval for predicting disease or future
disease of the new person/patient; and an alert unit configured with
registered contact number of the new person/patient for alerting the new
person/patient about disease or future disease and advising medical
assistance.
12
(N co
C C C
MC
M
fa w
fa
>
'Ii c
ai
21E ~21a
'4fa rii
J_-
C r
C r M td fa
'Af3 Eb f
tv
fII 3
r
CL L.J 03
Description
(N co
fa w
fa > 'Ii c
ai
21E ~21a
'4fa rii J_- C r C td fa 'Af3 Eb f r M
tv fII3
r
CL L.J 03
A 5G NETWORK-BASED SYSTEM AND METHOD FOR INTELLIGENT HEALTH-CARE APPLICATIONS USING MACHINE LEARNING APPROACH
The present disclosure relates toa 5G network-based system and method for intelligent health-care applications using machine learning approach.
Healthcare is rapidly evolving from a traditional hospital and specialist-focused model to a dispersed, patient-centric model. This fast evolution of the healthcare vertical is fuelled by advances in numerous technologies. Communication technology, among other things, have made it possible to provide tailored and distant healthcare services.
Existing communication technologies, on the other hand, are unable to meet the complex and dynamic demands placed on communication networks by a variety of smart healthcare applications.As a result, the next 5G network should be able to enable smart healthcare applications that meet the majority of the healthcare.
In the view of the forgoing discussion, it is clearly portrayed that there is a need to havea 5G network-based system and method for intelligent health-care applications using machine learning approach.
The present disclosureseeks to providea 5G network-based system and method for intelligent health-care applications and internet of things based notification using machine learning approach.
In an embodiment,a5G network-based system for intelligent health care applications using machine learning approachis disclosed.The system includes a database wirelessly connected with a plurality of health monitoring devices and server of various hospitals through a 5G network for receiving a set of health parameters along with disease types and physical records of patients. The system further includes a central processing unit in configuration with a machine learning approach for categorizing thereby interpreting data of patients stored in the database. The system further includes a control unit for receiving health report of a new person/patient thereby evaluating real time health of the new person/patient in a regular interval for predicting disease or future disease of the new person/patient. The system further includes an alert unit configured with registered contact number of the new person/patient for alerting the new person/patient about disease or future disease and advising medical assistance.
In an embodiment, health of the new person/patient is received by the control unit is detected by smart health monitoring devices, wherein health monitoring devices are glucometer, thermometer, heartrate sensor, blood pressure sensor, ECG device, EEG device, X-ray machine and the like.
In an embodiment, the 5G network is used to establish device to device connection, device to database connection, server to database connection, device-tower-database connection.
In an embodiment, the control unit is configured with the deep neural networkfor predicting disease or future disease of the new person/patient, which is trained on every health data process by the central processing unit for improvising evaluation of health real time health of new patient(s).
In an embodiment, the alert unit is configured with the control unit for alerting every new patient according to their health report in order to avoid any miscommunication to promote end to end secured delivery of report in minimum duration.
In another embodiment, a method for 5G network-based system for intelligent health-care applications is disclosed.The methodincludes receiving thereby storing a set of health parameters along with disease types and physical records of patients in a database from a plurality of health monitoring devices and server of various hospitals through a 5G network. The method further includes categorizing thereby interpreting data of patients stored in the database by employing a machine learning approach. The method further includes receiving health report of a new person/patient by a control unit thereby evaluating real time health of the new person/patient in a regular interval for predicting disease or future disease of the new person/patient. The method further includes alerting the new person/patient about disease or future disease and advising medical assistanceon registered contact number of the new person/patient using an alert unit.
An object of the present disclosure is to promote fast and efficient health care support.
Another object of the present disclosure is to facilitate real time health case detection and disease and early disease detection.
Yet another object of the present invention is to deliver an expeditious and cost-effective5G network-based method for intelligent health-care applications using machine learning approach.
To further clarify advantages and features of the present disclosure, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
These and other features, aspects, and advantages of the present disclosure will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:
Figure 1 illustrates a block diagram of a5G network-based system for intelligent health-care applications using machine learning approachin accordance with an embodiment of the present disclosure; and Figure 2 illustrates a flow chart of a5G network-based method for intelligent health-care applications using machine learning approachin accordance with an embodiment of the present disclosure.
Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present disclosure. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein.
For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.
It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not intended to be restrictive thereof.
Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.
The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by "comprises...a" does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.
Unless otherwise defined, 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. The system, methods, and examples provided herein are illustrative only and not intended to be limiting.
Embodiments of the present disclosure will be described below in detail with reference to the accompanying drawings.
Referring to Figure 1, illustrates a block diagram of a5G network based system for intelligent health-care applications using machine learning approachis illustrated in accordance with an embodiment of the present disclosure.The system 100 includes a database 102 which is wirelessly connected with a plurality of health monitoring devices 110 and server of various hospitals through a 5G network for receiving a set of health parameters along with disease types and physical records of patients. The disease type of the patient includes fever, viral infections or diseases, fungal infection or disease. The physical record of the patient includes BMI, age, and the like.
In an embodiment, a central processing unit 104is in configuration with a machine learning approach for categorizing thereby interpreting data of patients stored in the database 102.
In an embodiment, a control unit 106is connected with the central processing unit 104for receiving health report of a new person/patient thereby evaluating real time health of the new person/patient in a regular interval for predicting disease or future disease of the new person/patient.
In an embodiment, an alert unit 108is configured with registered contact number of the new person/patient for alerting the new person/patient about disease or future disease and advising medical assistance.
In an embodiment, health of the new person/patient is received by the control unit 106 is detected by smart health monitoring devices, wherein health monitoring devices are glucometer, thermometer, heartrate sensor, blood pressure sensor, ECG device, EEG device, X-ray machine and the like.
In an embodiment, the 5G network is used to establish device to device connection, device to database connection, server to database connection, device-tower-database connection.
In an embodiment, the control unit 106 is configured with the deep neural networkfor predicting disease or future disease of the new person/patient, which is trained on every health data process by the central processing unit 104 for improvising evaluation of health real time health of new patient(s).
In an embodiment, the alert unit 108 is configured with the control unit 106 for alerting every new patient according to their health report in order to avoid any miscommunication to promote end to end secured delivery of report in minimum duration. The alert unit 108 is equipped with the 5G network for transferring alert and medical report of the new patient. The 5G network promotes transmission of large information in a fast and effective way.
Figure 2 illustrates a flow chart of a5G network-based method for intelligent health-care applications using machine learning approach in accordance with an embodiment of the present disclosure.At step 202, the method 200includes receiving thereby storing a set of health parameters along with disease types and physical records of patients in a database 102 from a plurality of health monitoring devices 110 and server of various hospitals through a 5G network.
At step 204, the method 200includes categorizing thereby interpreting data of patients stored in the database 102 by employing a machine learning approach.
At step 206, the method 200includes receiving health report of a new person/patient by a control unit 106 thereby evaluating real time health of the new person/patient in a regular interval for predicting disease or future disease of the new person/patient.
At step 208, the method 200includes alerting the new person/patient about disease or future disease and advising medical assistanceon registered contact number of the new person/patient using an alert unit 108.
The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elementsmay well be combined into a single functional element. Alternatively, certain elementsmay be split into multiple functional elements. Elementsfrom one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no meanslimited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.
Benefits, other advantages, and solutions to problems have been described above with regard to specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims.
Claims (6)
1. A5G network-based system for intelligent health-care applications, the systemcomprises:
a database wirelessly connected with a plurality of health monitoring devices and server of various hospitals through a 5G network for receiving a set of health parameters along with disease types and physical records of patients; a central processing unit in configuration with a machine learning approach for categorizing thereby interpreting data of patients stored in the database; a control unit for receiving health report of a new person/patient thereby evaluating real time health of the new person/patient in a regular interval for predicting disease or future disease of the new person/patient; and an alert unit configured with registered contact number of the new person/patient for alerting the new person/patient about disease or future disease and advising medical assistance.
2. The systemas claimed in claim 1, whereinhealth of the new person/patient is received by the control unit is detected by smart healthmonitoring devices, wherein healthmonitoring devices are glucometer, thermometer, heartrate sensor, blood pressure sensor, ECG device, EEG device, X-ray machine and the like.
3. The systemas claimed in claim 1, wherein the 5G network is used to establish device to device connection, device to database connection, server to database connection, device-tower-database connection.
4. The systemas claimed in claim 1, wherein the control unit is configured with the deep neural networkfor predicting disease or future disease of the new person/patient, which is trained on every health data process by the central processing unit for improvising evaluation of health real time health of new patient(s).
5. The systemas claimed in claim 1, wherein the alert unit is configured with the control unit for alerting every new patient according to their health report in order to avoid any miscommunication to promote end to end secured delivery of report in minimum duration.
6. Amethod for 5G network-based system for intelligent health-care applications, the methodcomprises:
receiving thereby storing a set of health parameters along with disease types and physical records of patients in a database from a plurality of health monitoring devices and server of various hospitals through a 5G network; categorizing thereby interpreting data of patients stored in the database by employing a machine learning approach; receiving health report of a new person/patient by a control unit thereby evaluating real time health of the new person/patient in a regular interval for predicting disease or future disease of the new person/patient; and alerting the new person/patient about disease or future disease and advising medical assistanceon registered contact number of the new person/patient using an alert unit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021104781A AU2021104781A4 (en) | 2021-08-01 | 2021-08-01 | A 5g network-based system and method for intelligent health-care applications using machine learning approach |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2021104781A AU2021104781A4 (en) | 2021-08-01 | 2021-08-01 | A 5g network-based system and method for intelligent health-care applications using machine learning approach |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| AU2021104781A4 true AU2021104781A4 (en) | 2022-04-28 |
Family
ID=81259364
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| AU2021104781A Ceased AU2021104781A4 (en) | 2021-08-01 | 2021-08-01 | A 5g network-based system and method for intelligent health-care applications using machine learning approach |
Country Status (1)
| Country | Link |
|---|---|
| AU (1) | AU2021104781A4 (en) |
-
2021
- 2021-08-01 AU AU2021104781A patent/AU2021104781A4/en not_active Ceased
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11232855B2 (en) | Near-real-time transmission of serial patient data to third-party systems | |
| Vuppalapati et al. | The role of big data in creating sense ehr, an integrated approach to create next generation mobile sensor and wearable data driven electronic health record (ehr) | |
| US10831872B2 (en) | Automated voice-activated medical assistance | |
| WO2020047171A1 (en) | Medical device and method for diagnosis and treatment of disease | |
| US20020099273A1 (en) | System and user interface for use in providing medical information and health care delivery support | |
| CN107993727A (en) | A kind of data processing method, apparatus and system | |
| WO2009063285A1 (en) | Method and system for active patient management | |
| US10282519B2 (en) | Method and apparatus for providing nursing service | |
| US20220101968A1 (en) | Near-real-time transmission of serial patient data to third-party systems | |
| Alamri | Big data with integrated cloud computing for prediction of health conditions | |
| US20160070860A1 (en) | Structuring multi-sourced medical information into a collaborative health record | |
| US9978165B2 (en) | Dynamic presentation of waveform tracings in a central monitor perspective | |
| Husmann et al. | On the importance of clinical notes in multi-modal learning for EHR data | |
| US20220189637A1 (en) | Automatic early prediction of neurodegenerative diseases | |
| AU2021104781A4 (en) | A 5g network-based system and method for intelligent health-care applications using machine learning approach | |
| JP2008016021A (en) | Method for clinical interpretation and examination of patient data, and its system | |
| WO2007106228A2 (en) | Method and system for routing information to an appropriate care provider | |
| US20130073304A1 (en) | Method and system for auto rebinding of patient demographic details to patient monitoring devices | |
| US20160371457A1 (en) | System and Method for Data Analyzing of Health-Related Data | |
| KR102418699B1 (en) | Method for determine patient's emergency based on smart device and server thereof | |
| US20160004822A1 (en) | Medical information system and a method for promoting patient compliance and for selectively populating an electronic medical record system with data | |
| CN109559790A (en) | A kind of health medical treatment management method and system | |
| US20210407667A1 (en) | Systems and methods for prediction of unnecessary emergency room visits | |
| Percival et al. | Enabling the integration of clinical event and physiological data for real-time and retrospective analysis | |
| US20220215952A1 (en) | Wireless patient health monitoring and management system using iot and 6g technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| FGI | Letters patent sealed or granted (innovation patent) | ||
| MK22 | Patent ceased section 143a(d), or expired - non payment of renewal fee or expiry |