CN113506622A - Intelligent diagnosis and analysis system and use method thereof - Google Patents

Abstract

The invention discloses an intelligent diagnosis and analysis system and a use method thereof, wherein the intelligent analysis system comprises: the device comprises a database unit, an information acquisition unit, a model unit and an analysis unit. The use method of the intelligent diagnosis and analysis system comprises the steps of establishing a diagnosis database, obtaining disease information of a patient, setting a diagnosis and analysis model, and giving a diagnosis and analysis result according to the disease information of the patient, the relation between the disease information and the disease and the diagnosis and analysis model. According to the intelligent diagnosis and analysis system and the use method thereof, the whole process comprehensive analysis and recommendation are carried out on the aspects of safety, effectiveness, economy, suitability and the like in the diagnosis process of the patient on the basis of technical data such as diagnosis and treatment specifications, medical personnel and the patient can be helped to quickly and accurately obtain scientific diagnosis paths and diagnosis conclusions, and the accuracy and timeliness of diagnosis are effectively improved.

Description

Intelligent diagnosis and analysis system and use method thereof

Technical Field

The invention relates to the technical field of intelligent medical information processing, in particular to an intelligent diagnosis and analysis system and a using method thereof.

Background

The diagnosis is a diagnosis conclusion given by a doctor according to the health condition of the patient and the disease information. The correctness of the diagnosis conclusion directly affects the effective treatment of the disease, the reasonable allocation of medical resources, the safety and health of the patient, and the like, and is the key for ensuring the medical quality, controlling the unreasonable medical expense and maintaining the rights and interests of the patient. According to the condition of the patient, the establishment of a proper diagnosis scheme is important for the patient to confirm diagnosis and perform symptomatic treatment as soon as possible. In the process of diagnosis, inquiry, physical examination, blood and urine routine examination are also common methods for acquiring symptoms and index information of patients, and with the increasingly improved hospital equipment, X-ray chest fluoroscopy, electrocardiographic examination and ultrasonic examination are regarded as methods for acquiring information by most doctors routinely. The continuous emergence and widespread use of various diagnostic tools inherently provides more information at an early stage, but sometimes places an unnecessary burden on the patient. Meanwhile, the unreasonable diagnosis method may bring unnecessary risks and damages to the patient and delay the timely treatment of the patient, so whether the diagnosis scheme is reasonable also relates to the effective treatment of diseases, the reasonable allocation of medical resources and the safety and health of the patient.

In the diagnosis process, doctors should analyze possible diseases of patients based on clinical conditions of the patients and combining individualized information of the patients, and make relevant diagnosis schemes according to diagnosis needs, obtain relevant information and give correct diagnosis conclusions. Meanwhile, factors such as the application range of various diagnostic methods related to the diagnostic scheme, contraindications, cautions, adverse reactions, time, cost, potential safety hazards, use limitations and the like are considered, a suitable diagnostic method or a combination thereof is selected, the diagnostic method which is seriously harmful to the patient is eliminated, and the diagnostic method which is potentially dangerous to the patient needs to fully evaluate risks and balance necessity. In addition, the patient's medical insurance and financial payment capabilities should be considered as well as the suitability of the diagnostic protocol. Only by comprehensively considering the factors, the optimal target can be achieved, the disease condition judgment of the patient can be rapidly and accurately obtained, and the rights and interests of the patient are fully guaranteed.

In the actual diagnosis process, the medical staff may not know the specific contents of the disease diagnosis sufficiently, or have insufficient individual information for the patient, or have human errors, etc., which may cause the phenomena of inaccurate diagnosis conclusion and unreasonable diagnosis scheme. Therefore, an intelligent diagnosis and analysis system is urgently needed, and is an important method for guaranteeing the accuracy of the diagnosis result and the rationality of the diagnosis scheme of the patient, and comprehensively analyzes and recommends the whole process of the aspects of safety, effectiveness, economy, suitability and the like in the diagnosis process of the patient on the basis of technical data such as diagnosis and treatment specifications. Especially, with the development and application of modern information technology, the appearance of intelligent medical analysis systems makes it possible to comprehensively grasp massive medical data and patient information, and will gradually play a great role in ensuring the accuracy and reasonableness of patient diagnosis.

Disclosure of Invention

The main purposes of the invention are: aiming at the related risks caused by inaccurate and untimely diagnosis conclusion and unreasonable and non-compliant aspects such as effectiveness, safety, economy, suitability and the like of a diagnosis scheme possibly existing when a patient diagnoses diseases, an intelligent diagnosis and analysis system is provided, and diagnosis and analysis are intelligently performed according to the actual situation of the patient, so that medical personnel and the patient are helped to quickly and accurately obtain scientific diagnosis paths and diagnosis conclusions, the phenomena of inaccurate diagnosis conclusion and unreasonable diagnosis schemes are avoided, and the accuracy and timeliness of diagnosis are effectively improved.

To achieve the above object, the present invention provides an intelligent diagnostic and analysis system, comprising:

a database unit for storing a diagnosis database including a relation of disease information and a disease;

an information acquisition unit for acquiring disease information of a patient;

a model unit for setting a diagnosis analysis model for giving a diagnosis conclusion including at least one parameter of possibility/probability of a disease, severity, urgency, difference of treatment protocol, cost;

and the analysis unit is used for giving a diagnosis analysis result according to the patient disease information, the relationship between the disease information and the disease and the diagnosis analysis model.

An intelligent diagnostic analysis system as described above, the diagnostic analysis results comprising: judging whether a diagnosis conclusion can be obtained according to the existing information, evaluating whether the existing diagnosis conclusion is correct, recommending the diagnosis conclusion, and recommending at least one of diagnosis schemes for continuing diagnosis.

In the above intelligent diagnosis and analysis system, the analysis unit sets corresponding levels/scores according to different analysis results of at least one analysis item of possibility/probability, severity, urgency, treatment scheme difference and treatment cost of a patient suffering from different diseases under different disease information/patient information conditions, and when performing diagnosis and analysis, can calculate comprehensive levels/scores of different diagnosis results under the disease information/patient information conditions according to the levels/scores corresponding to the diagnosis results obtained by diagnosis and analysis in each analysis item and a set diagnosis and analysis model, so that the analysis unit can provide the diagnosis and analysis results.

The intelligent diagnosis and analysis system further comprises a module for evaluating the original diagnosis and analysis result or performing the diagnosis and analysis again to obtain a new diagnosis and analysis result according to the new patient disease information obtained in the treatment process or the treatment result or according to the actual treatment effect of the diagnosis conclusion.

The intelligent diagnosis analysis system as described above, the diagnosis database further includes a relationship between the disease and the diagnosis plan, and the analysis unit analyzes a possible disease range of the patient according to the disease information of the patient and the relationship between the disease information and the disease, and then obtains the recommendation list of the diagnosis plan according to the possible disease range of the patient and the relationship between the disease and the diagnosis plan.

The intelligent diagnosis analysis system as described above, the diagnosis database further includes relevant rules of rationality and compliance of diagnosis schemes, and the analysis unit optimizes the recommendation list of diagnosis schemes according to the relevant rules of rationality and compliance of diagnosis schemes.

The intelligent diagnosis analysis system comprises the following relevant rules of reasonable and compliant diagnosis schemes: at least one of rules related to applicability, rules related to contraindications, rules related to need of caution/attention, rules related to interaction, rules related to allergy, rules related to time, rules related to method of development/method of use, rules related to dosage, rules related to adverse reaction, rules related to preparation/protective measures, rules related to suitability/comfort/compliance, rules related to medical insurance/welfare, rules related to economic regulation, and rules related to administrative management.

The intelligent diagnosis and analysis system as described above, the database unit further stores a patient personal information database, and the patient personal information database includes the relevant information of the patient, and is used for providing or supplementing the relevant information of the patient during the diagnosis and analysis.

In the above intelligent diagnosis and analysis system, the database unit further stores a diagnosis multidimensional element attribute dictionary, and is used for processing matching/comparison between the acquired information and related information and rules in the database unit.

The invention also provides a use method of the intelligent diagnosis and analysis system, which comprises the following steps:

step 1, establishing a diagnosis database, wherein the diagnosis database comprises the relation between disease information and diseases;

step 2, acquiring disease information of a patient;

step 3, setting a diagnosis and analysis model, wherein the diagnosis and analysis model is used for giving a diagnosis conclusion and comprises at least one parameter of possibility/probability, severity, urgency, treatment scheme difference and cost of diseases;

and 4, giving a diagnosis analysis result according to the disease information of the patient, the relation between the disease information and the disease and the diagnosis analysis model.

The method for using the intelligent diagnosis and analysis system, wherein the method further comprises a recommended diagnosis scheme, and the recommended diagnosis scheme comprises the following steps:

step 101, analyzing whether a diagnosis can be made based on existing patient disease information? If yes, executing step 103, if no, executing step 102;

102, recommending a diagnosis scheme suitable for a patient according to the existing patient disease information, acquiring more patient disease information through the diagnosis scheme, and returning to the step 101;

and 103, obtaining a diagnosis conclusion and finishing the recommendation of the diagnosis scheme.

The invention relates to an intelligent diagnosis and analysis system and a using method thereof, wherein the intelligent analysis system comprises: the device comprises a database unit, an information acquisition unit, a model unit and an analysis unit. The use method of the intelligent diagnosis and analysis system comprises the steps of establishing a diagnosis database, obtaining disease information of a patient, setting a diagnosis and analysis model, and giving a diagnosis and analysis result according to the disease information of the patient, the relation between the disease information and the disease and the diagnosis and analysis model. According to the intelligent diagnosis and analysis system and the use method thereof, the aspects of safety, effectiveness, economy, suitability and the like in the diagnosis process of the patient are comprehensively analyzed and recommended in the whole process on the basis of technical data such as diagnosis and treatment specifications, the phenomena that the diagnosis conclusion is inaccurate and the diagnosis scheme is unreasonable due to the fact that medical staff cannot know the specific content of disease diagnosis sufficiently, or the individual information of the patient is not mastered sufficiently, or human errors occur in the actual diagnosis process can be avoided, so that the medical staff and the patient can be helped to quickly and accurately obtain scientific diagnosis paths and diagnosis conclusions, and the accuracy and timeliness of diagnosis are effectively improved.

Drawings

FIG. 1 is a block diagram of an intelligent diagnostic and analysis system of the present invention.

FIG. 2 is a flow chart of a method of using an intelligent diagnostic and analysis system of the present invention.

Detailed Description

To further explain the technical means and effects of the present invention adopted to achieve the intended purpose, the following detailed description of the embodiments of the present invention is provided in conjunction with the accompanying drawings and examples.

A first embodiment of the present invention is described with reference to fig. 1. FIG. 1 is a block diagram of an intelligent diagnostic and analysis system of the present invention. As shown in the drawings, an intelligent diagnostic analysis system of the present invention includes:

a database unit 11 for storing a diagnosis database comprising relations of disease information and diseases.

An information acquisition unit 12 for acquiring disease information of the patient.

A model unit 13 for setting a diagnostic analysis model for giving a diagnostic conclusion including at least one parameter of likelihood/probability, severity, urgency, treatment protocol difference, cost of the disease.

And the analysis unit 14 is used for giving a diagnosis analysis result according to the patient disease information, the relationship between the disease information and the disease and the diagnosis analysis model.

First, a diagnostic database needs to be built.

In the present invention, the diagnostic database may include: the relationship between the disease information and the disease can also comprise the relationship between the disease and a diagnosis scheme, information and rules related to the reasonability and compliance of the diagnosis scheme, and the like. The method specifically includes various related element attributes and values/ranges/calculation methods/sources/limiting conditions/exclusion conditions of the various element attributes, and interrelations/interactions/interconversion/rules/calculation methods among various/various groups/various types of element attributes.

The diagnosis is that a doctor can directly give a diagnosis conclusion based on the clinical condition of a patient and also can continuously obtain new patient disease information through a diagnosis scheme by combining individualized information of the patient until the diagnosis conclusion can be given. Meanwhile, when new patient disease information is acquired through a diagnosis scheme, factors such as application range of various diagnosis methods, contraindications, cautionary matters, adverse reactions, time, cost, potential safety hazards, use limitations and the like need to be considered, and a scheme formed by selecting a suitable diagnosis method or a combination of the diagnosis methods is selected. The diagnostic method may include: examination, interrogation, observation, detection, monitoring, inspection, experiment, test, surgery (obtaining tissue for diagnosis), and the like.

The relationship of disease information to disease includes: different disease information corresponds to possible diseases, and the disease information required when diagnosis can be confirmed. The relationship between disease information and possible relationships in the disease and the relationship between the diagnosis also need to take into account the balance between likelihood/probability of disease, severity, urgency, treatment regimen variation, and treatment cost. Since the more information that is acquired, the more accurate the diagnosis, but the higher the cost, the lower the probability of being acquired, and the less information that is acquired, the lower the accuracy of the diagnosis. The same disease information may correspond to a plurality of different diseases or disease combinations, each corresponding disease or disease combination having a different accuracy, risk, and cost of diagnosis/treatment, including time cost and expense cost, etc. Different parameters can be configured in advance or through big data analysis to determine different diagnosis strategies and analysis methods adopted in different situations.

The strategy and analysis method can be as follows: setting analysis items such as possibility/probability, severity, urgency, treatment scheme difference and cost of diseases, comprehensively considering each analysis item, and finding appropriate balance among the analysis items to ensure the best comprehensive effect. The comprehensive consideration of each analysis item can be to balance different elements of each analysis item through preset parameters, or to modify and replace preset parameters according to actual conditions, so as to ensure the balance of different elements of each analysis item under actual conditions. The setting, modification and alternation of the relevant parameters can be obtained by experts according to experience or can be obtained by artificial intelligence according to big data analysis. The setting, modification and alternation of the relevant parameters can be completed by the model unit 13, or can be completed by the analysis unit 14.

For example: the disease information corresponds to a plurality of possible diseases or disease ranges, and not only can continuously acquire more disease information through various diagnosis methods to increase the accuracy of diagnosis and eliminate impossible diseases, but also the acquisition cost of more disease information is greatly increased, the acquisition possibility is reduced, and new risks such as delay of treatment due to slow diagnosis and missing of the optimal treatment opportunity are brought, so that the more disease information is acquired to more accurately diagnose without considering other analysis items, and the actual diagnosis process is unrealistic. Therefore, it is sometimes necessary to develop empirical treatment based on limited disease information, considering possibility/probability, severity, urgency, treatment scheme difference, treatment cost, etc. of the disease, wherein the empirical treatment is actually a stage conclusion and measure for the possible disease, especially the severe condition, before diagnosis, and new disease information is continuously acquired during the development of treatment according to the stage conclusion, such as: new examination/test results, new symptoms, new feelings, etc. by adding new disease information to existing information and analyzing, new conclusions can be analyzed, and diagnosis conclusions and adjustments of diagnosis schemes can be made in time. When an exclusive conclusion can be obtained according to the disease information of the patient based on different diagnosis models and different equilibrium parameters, the diagnosis analysis result can be given.

Also, the relationship between disease and diagnostic protocols requires a balance between accuracy, risk, and cost. The relationship of disease to diagnostic protocol includes the appropriate diagnostic protocol required for different diseases or disease ranges. Also, analysis items such as possibility/probability, severity, urgency, treatment plan difference, treatment cost, etc. of diseases need to be comprehensively considered, and a proper balance is found among the analysis items, so that the comprehensive effect is the best.

The diagnostic protocol may be a static set or sets of protocols or may be a dynamic diagnostic path. Static protocols are defined as fixed diagnostic protocols that are developed using a corresponding fixed diagnostic protocol or a combination thereof for each clinical condition of the patient. The dynamic scheme is to make a diagnosis scheme step by step in the diagnosis process, and make a next step of the diagnosis scheme or adjust and modify the existing diagnosis scheme in a targeted manner according to new information obtained by the diagnosis scheme in the previous step, and the diagnosis scheme corresponds to different diagnosis schemes in the next step. It is also possible to follow the disease progression, different stages of the disease course, patient information, performance or a combination thereof, and may also include the disease progression/change during the course of treatment/treatment attempts, the resulting new disease information, and select different diagnostic pathways or recommend new diagnostic protocols for this information. In the present invention, the range/number/intensity of problems to be solved at each step of the diagnostic protocol, etc. can be set.

The diagnosis database of the invention is based on various diagnosis and treatment standards, diagnosis and treatment specifications, guidelines, industry specifications, textbooks, clinical treatment routes, drug specifications, medical equipment use/operation specifications, medical instrument use specifications, surgical operation specifications, examination/inspection specifications, prescription sets, pharmacopoeias, expert consensus, expert experience, conference disciplines and consensus inside the conjunctions/hospitals/departments, treatises, monographs, inventions, scientific inferences, experimental reports, data analysis reports, test reports, examination reports, approval documents, relevant regulations, relevant guidance opinions, relevant policies, relevant regimes, relevant catalogs, relevant literature data, relevant price regulations, relevant price catalogs, relevant invitation results, relevant object price policies, relevant insurance clause payment protocols, relevant insurance payment protocols, The system comprises a relevant bidding result, a relevant purchasing catalogue, an evaluation/inspection result/monitoring report/safety report of a relevant doctor/nurse/checker/pharmacist/nursing staff/patient/salesperson, a method based on evidence-based medicine, probability speculation based on the existing data, a database established by sources such as various weights/various levels/various sequencing and the like needing to be set manually, a database established based on information reforming/information analysis/big data analysis, a database established by artificial intelligence deep learning, a database obtained by data mining analysis, rules and indexes manually set after data statistical analysis/artificial intelligence deep learning, or the relevant information and rules which are continuously accumulated and refined in the disease treatment process by the clinician and the pharmacist. The diagnostic database may also be a database built by a combination of the above methods. The database can be updated according to versions or can be updated in real time according to actual data. The diagnostic database may be a relational database or a non-relational database; the database can be a table database, a graph database or a knowledge map database; the related data may be structured data or unstructured data.

Relevant rules for the rationality and compliance of diagnostic protocols in the diagnostic database include: at least one of the rules related to applicability, contraindications, cautious/cautious, interaction, allergy, time, method of development/use, dosage, adverse reactions, readiness/protection, suitability/comfort/compliance, medical insurance/welfare, economic regulation, administrative regulation, and other rules related to the rationality and compliance of the diagnostic protocol.

The various diagnosis relevant elements and the relationship of diagnosis to disease information and diagnosis to disease involved in the diagnosis database may include: the conditions/requirements/attributes/values of the diagnosis method such as examination/inspection/operation, such as examination time, method, precautions, required drugs/medical devices, manufacturer, specification, dosage form, daily frequency, daily dosage, daily dose, administration method, administration route, etc. Further comprising: basic information of a patient, population information, genetic-related information, disease information, medical history information, medication history information, medical instrument use history information, operation items, symptoms, indices, feelings, physical conditions, operation subjects, operation methods, operation targets, physiological development information, marriage and care information, physiological conditions, psychological/intellectual conditions, life/work/study/sport/entertainment information, environmental information, drug/medical instrument/health product/cosmetic use-related information, medical insurance-related information, medical expense payment ability/will, medical institution information, medical staff information, medical instrument/consumable/instrument/drug/implant required for a diagnostic plan, expense for a diagnostic plan, care, risk assessment, staging, medical history, phase, anesthesia, respiration, hemostasis, infection prevention, pain, emergency measures, index control, preparation and requirements, training, indications/indications, contraindications, related protection and first aid, nutritional support, doctor level and authority, ancillary software, images, and other essential information.

In the present invention, the crowd information may include specific crowd information such as a specific age, gender, development status, marital status, fertility status, work status, learning status, exercise status, life status, physiological status, psychological status, and genetic status. The genetically related information includes: genetic information, genetic information mutation/change information, genetic defect information, genetic medical history, family medical history, and the like. The disease information includes: disease, diagnosis, symptom type, symptom, index, pulse condition, tongue diagnosis, etc. The medical history information includes medical history, surgical history, radiotherapy history, chemotherapy history, psychotherapy history, physical therapy history, immunotherapy history, gene therapy history and the like. The medication history information includes: medication history, drug efficacy, adverse drug reactions, drug allergy history, drug tolerance and the like. The medical instrument use history information includes: medical instrument use history, medical instrument use curative effect, medical instrument use adverse reaction, medical instrument tolerance and the like. The operation items include operation, examination, test, detection, operation, health promotion, rehabilitation, psychotherapy, radiotherapy, chemotherapy, physiotherapy, thermotherapy, phototherapy, magnetotherapy, electrotherapy, cryotherapy, electromagnetic therapy, phonotherapy, immunotherapy, gene therapy, weight reduction, body building, shaping, and skin caring. The physiological development information includes: growth and development conditions, physiological stages, fertility and the like. The marriage and childbirth information comprises marriage history, birth history, sexual life and the like. The physiological conditions include: physical performance, nutritional status, hearing, vision, taste, smell, touch, respiration, motor coordination, digestion, absorption, excretion, sexual function, and the like, and levels of related abilities. Psychological/intellectual status includes: psychological disorders, mood, feeling, intelligence, attention, memory, perception, communication ability, expression ability, and the like. Life/work/learning/sports/entertainment information includes: diet, work and rest, sleep, work, study, entertainment, sports and other related information. The environment information includes: temperature, humidity, air pressure, season, altitude, air quality, terrain, topography, oxygen content, light, ultraviolet light, radiation, electromagnetic waves, noise, epidemics, vegetation and other information. The medical insurance-related information includes medical welfare, medical insurance, business insurance, and the like. The medical institution information includes medical institution level, specialty, attribute, region, department, etc. The medical staff information includes: age, gender, job title, professional qualification, professional training, protective measures and the like. The medical device comprises: active surgical instruments, passive surgical instruments, neurological and cardiovascular surgical instruments, orthopedic surgical instruments, radiation therapy instruments, medical imaging instruments, medical examination and monitoring instruments, respiratory/anesthesia and emergency medical instruments, physical therapy instruments, blood transfusion/dialysis and extracorporeal circulation instruments, medical instrument sterilization instruments, active implant instruments, passive implant instruments, injection/care and protection instruments, patient-carrying instruments, ophthalmic instruments, dental instruments, gynecological/assisted reproduction and contraception instruments, medical rehabilitation instruments, traditional Chinese medicine instruments, medical software, clinical laboratory instruments, surgical robots, nursing robots and other products belonging to the category of medical instruments or similar medical instruments, and other products with similar effects, including components or accessories, consumables, and the like. The implant comprises: grafts, cultures, gene vectors, implant chips, implant devices/apparatus, and the like. Nutritional support includes: detecting water, heat, protein, trace elements, sugar, salt, fat, carbohydrate, minerals, amino acids, vitamins, content standard, and supplement dosage.

The rules in the diagnosis database also include the condition that each element needs to be combined to be effective, the related rules can be defined by the comprehensive conditions after the elements are combined according to the multi-level and/or non-relationship and the relationship defined by the related formula, and also include the condition that the related rules are related to the time dimension.

Next, disease information of the patient is acquired by the information acquisition unit 12.

The patient disease information may include: patient basic information, indices, parameters, states or conditions of the patient's various physiological/psychological/learning/work/physical/sleep/exercise/mood/metabolism/visual/hearing/mental/attention/appetite/immunity/growth/memory/fertility/genetic related information, etc.; information obtained by inquiry, examination, detection, test, experiment, operation, evaluation and observation of diseases/symptoms/indexes and the like; information relating to the patient's growth/development/fertility/contraception/assisted reproduction/psychological/learning/work/exercise/entertainment/nutritional/caloric requirements, etc.; surgery/operation/examination/detection/monitoring/evaluation/analysis/prediction/physiotherapy/thermotherapy/phototherapy/magnetotherapy/electrotherapy/rehabilitation/healthcare/immunotherapy/gene therapy information of a patient; the medicine/medical instrument/health product/cosmetic of the patient, etc.

The sources from which patient disease information is obtained may be: patient-related symptoms, related indicators, feelings, states, physiological functions self-statement; the state and the requirement of the patient for learning, working, living, sports, etc. are self-describing; advice prescribed by medical staff; patient medical records, electronic medical records, diagnosis reports, examination results, inspection results, monitoring results, assessment reports; obtaining from a patient personal information database; information obtained by means of interrogation, examination, detection, testing, experimentation, surgery, assessment, evaluation, observation, etc.; preset time, season, time of day, interval, period and other information; and the preset ways of monitoring the change of various physiological and pathological indexes and the like.

After that, a diagnostic analysis model is set by the model unit 13.

In the present invention, the diagnostic analysis model is used to give a diagnostic conclusion including at least one parameter of likelihood/probability, severity, urgency, treatment variation, cost of the disease. The diagnostic analysis model can be established by acquiring the combination of dimensional elements of a large number of diagnostic examples, then performing data set, evaluating whether common characteristics exist or not, and establishing the diagnostic analysis model by using various related statistical methods, big data monitoring and other methods for the combination of the elements with the common characteristics. The model can be established based on a evidence-based medical method, or based on probability speculation of existing data, and can be established by sources such as various weights, various levels, various sequencing and the like which need to be set manually, or established based on information reformation, information analysis and big data analysis, or established through artificial intelligence deep learning, or obtained through data mining analysis, or manually set through data statistical analysis and artificial intelligence deep learning, or established through continuous accumulation and refinement in the disease diagnosis and treatment process by clinicians and pharmacists. The parameters of the diagnostic and analytical model can be manually set by experts, or obtained through data statistics/analysis, or obtained through information reformation/big data analysis, or obtained through artificial intelligence deep learning/optimization, and can be continuously accumulated and optimized in the using process.

In the present invention, the diagnostic analysis model may also be used to analyze the range of possible diseases for a patient. According to different analysis results of at least one analysis item of the possibility/probability, the severity, the urgency, the treatment scheme difference and the treatment cost of different diseases of the patient under the condition of different disease information/patient information, corresponding grades/scores are respectively set, and when a possible disease range of the patient is analyzed, the comprehensive grades/scores of different possible disease ranges under the condition of the disease information/patient information can be calculated according to the grades/scores corresponding to the analysis items of the different possible disease ranges and a set diagnosis analysis model, so that the possible disease range of the patient can be given according to preset parameters.

Finally, diagnostic analysis is performed by the analysis unit 14, giving diagnostic analysis results based on the patient's disease information, the relationship of the disease information to the disease, and the diagnostic analysis model.

In the intelligent diagnosis and analysis system of the present invention, the analysis unit 14 may further set corresponding levels/scores according to different analysis results of at least one analysis item of the possibility/probability, the severity, the urgency, the difference in the treatment scheme, and the treatment cost of the patient suffering from different diseases under different disease information/patient information conditions, and when performing diagnosis and analysis, may calculate the comprehensive levels/scores of different diagnosis conclusions under the disease information/patient information conditions according to the levels/scores corresponding to the diagnosis conclusions analyzed by the diagnosis and analysis items and the set diagnosis and analysis model, so that the analysis unit can provide the diagnosis and analysis results. May be used to give a comprehensive recommendation or comprehensive prioritization of diagnostic conclusions, including comparisons between different diagnostic conclusions. The level/score corresponding to each analysis item and the setting of each parameter in the diagnostic analysis model may be performed by the analysis unit 14 or the model unit 13.

The basis for recommending or confirming the diagnosis conclusion of the intelligent diagnosis and analysis system can be that the comprehensive grade/score of the diagnosis conclusion reaches a preset threshold value, or the comprehensive grade/score of the diagnosis conclusion is optimal, the difference between the comprehensive grade/score of the diagnosis conclusion and the comprehensive grade/score of other diagnosis conclusions is larger than the preset threshold value, or the comprehensive grade/score and the score of an individual analysis item selected according to the actual situation are combined to reach the set standard. The intelligent diagnosis analysis system of the invention can also carry out treatment aiming at a plurality of possible diagnosis conclusions in a combined way, thereby saving medical resources, such as: treatment regimens that differ only slightly between the multiple possible diagnostic conclusions and are of little severity and urgency can be targeted for combination therapy.

The diagnostic assay results include: judging whether a diagnosis conclusion can be obtained according to the existing information, evaluating whether the existing diagnosis conclusion is correct, recommending the diagnosis conclusion, and recommending at least one of diagnosis schemes for continuing diagnosis. For example: the intelligent diagnosis and analysis system can judge whether a diagnosis conclusion can be obtained according to the existing information by performing diagnosis and analysis on the existing disease information, can provide a recommended diagnosis conclusion if the diagnosis conclusion can be obtained, and can recommend to continue diagnosis and recommend a proper diagnosis scheme if the diagnosis conclusion cannot be obtained; the existing disease information can be diagnosed and analyzed to judge whether the existing diagnosis conclusion is correct or not, and the method can be used for recommending, auditing and evaluating the diagnosis conclusion.

In the invention, the diagnosis analysis result given by the intelligent diagnosis analysis system can be used for assisting in reminding, warning, limiting, prohibiting, assisting and guiding patients/doctors/nurses/caregivers to diagnose. It can also be used as a data base for patient/doctor/nurse/caregiver to discuss diagnosis and advanced post reply/auto reply with the recommendation/administration/guidance/counseling post or secondary recommendation/administration/guidance/counseling center. And the evaluation result can also be used as the basis for professional level evaluation/professional normative evaluation/performance assessment of personnel such as doctors, nurses, caregivers and the like afterwards. And can also be used as the basis for selling or refusing the selling of the vending machine/electric business/pharmacy/medical institution. The intelligent vending machine can also be communicated with various information systems/information platforms/various vending machines/intelligent wearable devices/intelligent household devices/intelligent medical devices/remote control medical devices to serve as configurable control items of relevant operations or processes under the triggering of the systems or the relevant devices, such as automatic vending, intelligent reminding, intelligent starting, intelligent closing and the like. The method can also be used as the basis for evaluating, checking, supervising, law enforcement, management, referee medical institution/drugstore/medical instrument retail store related business behaviors of medical insurance management institution/medical insurance company/health administration/health management department/credit evaluation institution/grade review institution/judicial institution, the treatment/rehabilitation/health care/examination of guardians/family doctors/family drugstores/health managers/family nursing management patients, the diagnosis part involved in the health management/disease management of patients by the intelligent health management system/disease management system, the research institution/research personnel/production enterprise/sales enterprise/use institution/purchasing institution/patients/doctors/nurses/sales personnel and the like The data basis of object selection/evaluation/design/research/development/sale can also be used for data basis of medical insurance management/medical insurance company/price management/health administration/medical institution for making operation-related policy/regulation/payment range/payment rate/payment amount/use range and the like. The feedback objects and applications of the analysis items and the analysis results can also be set, the analysis results of the analysis items are fed back to different departments and different posts according to the requirements of patients, the processing authority and the flow of each department and post and the processing time limit and the processing requirements of each link are set, and various corresponding analysis result reports can also be generated according to the management requirements. The application of the rationality analysis to each analysis item may be a mode of recommendation in advance/in advance or a mode of comment after the fact. According to the analysis and the evaluation results, a normative evaluation report of the diagnosis and analysis is provided for medical administration staff, medical insurance institutions, medical insurance management staff and circulation field management staff, and various possible illegal and illegal behaviors are prompted, so that support is provided for further normative diagnosis and analysis.

The intelligent diagnosis and analysis system of the invention can also comprise a new diagnosis and analysis result which is obtained according to the new patient disease information obtained in the treatment process or the treatment result or the actual treatment effect of the diagnosis conclusion, and the original diagnosis and analysis result is evaluated or the new diagnosis and analysis result is obtained by carrying out the diagnosis and analysis again. The original diagnosis and analysis result is analyzed and evaluated through new disease information or actual treatment effect, and the diagnosis and analysis result can be adjusted and corrected at any time, so that the correctness of the analysis result is ensured.

The intelligent diagnosis and analysis system can also carry out regression verification and correction on the treatment result, the diagnosis conclusion and the diagnosis scheme through big data analysis, can carry out analysis and evaluation on the diagnosis and analysis model, and improves and adjusts the balance of analysis items such as possibility/probability, severity, emergency degree, treatment scheme difference, cost and the like of diseases and preset parameters, so that the effect of the diagnosis and analysis model is better.

In the present invention, the diagnostic analysis model includes both a diagnostic analysis model for a single disease species and a diagnostic analysis model for a complex/mixed disease, and for the complex/mixed disease, the influence of the complex/mixed disease on the disease information and each parameter needs to be considered comprehensively, so the complexity of the diagnostic analysis model is also increased greatly.

The intelligent diagnosis and analysis system can also recommend a diagnosis scheme suitable for a patient according to the diagnosis and analysis result. The recommended diagnostic protocol includes the steps of:

step 101, analyzing whether a diagnosis can be made based on existing patient disease information? If yes, executing step 103, if no, executing step 102;

102, recommending a diagnosis scheme suitable for a patient according to the existing patient disease information, acquiring more patient disease information through the diagnosis scheme, and returning to the step 101;

and 103, obtaining a diagnosis conclusion and finishing the recommendation of the diagnosis scheme.

The diagnosis database also comprises the relation between the diseases and the diagnosis schemes, and the analysis unit analyzes the possible disease range of the patient according to the disease information of the patient and the relation between the disease information and the diseases, and then obtains a diagnosis scheme recommendation list according to the possible disease range of the patient and the relation between the diseases and the diagnosis schemes. The diagnosis database also comprises relevant rules of reasonability and compliance of the diagnosis scheme, and the analysis unit optimizes the recommendation list of the diagnosis scheme according to the relevant rules of reasonability and compliance of the diagnosis scheme.

The diagnosis scheme is a scheme for obtaining new disease information by various diagnosis methods according to the disease information of different patients, corresponding diseases or disease combinations and the individual actual conditions of different patients to obtain a diagnosis conclusion. The diagnostic scheme can be established by acquiring the combination of all dimensional elements after acquiring a large number of diagnostic examples, performing data set, evaluating whether common characteristics exist or not, and establishing the diagnostic scheme by using various related statistical methods, big data monitoring and other methods for the element combination with the common characteristics.

The diagnosis database comprises a corresponding relation between the disease information and the possible disease range, a corresponding relation between the possible disease range and the diagnosis scheme, the possible disease range of the patient can be analyzed through the disease information of the patient, and the diagnosis scheme required by the patient can be analyzed through the possible disease range of the patient. The diagnosis database can also comprise the corresponding relation between the disease information and the diagnosis scheme, and the diagnosis scheme required by the patient can be analyzed directly through the disease information of the patient. Certainly, the obtained diagnosis schemes are only subjected to preliminary analysis, a plurality of diagnosis schemes obtained through the preliminary analysis may be available, some diagnosis schemes unsuitable for the actual situation of the patient are also included, the diagnosis schemes which are seriously harmful to the patient are eliminated through comparison with relevant information and rules which are reasonable and compliant with the diagnosis schemes in a diagnosis database, and the diagnosis schemes which have potential risks to the patient need to be fully evaluated and the necessity to be weighed, so that the diagnosis schemes which are really suitable for the patient can be obtained.

Relevant rules for rationality and compliance of a diagnostic protocol may include: at least one of the rules related to applicability, contraindications, cautious/cautious, interaction, allergy, time, method of development/use, dosage, adverse reactions, readiness/protection, suitability/comfort/compliance, medical insurance/welfare, economic regulation, administrative regulation, and other rules related to the rationality and compliance of the diagnostic protocol.

Relevant rules for applicability in relevant rules for rationalization and compliance of diagnostic protocols in the diagnostic database and elements thereof may include: the system comprises the diagnosis scheme, a diagnosis system and a diagnosis system, wherein the diagnosis scheme comprises the necessity, level, degree, sequencing, effectiveness of the diagnosis scheme, the suitability evaluation of patients/operators/doctors/pharmacists/nurses/caregivers, the reasonability and compliance of applicable groups, the reasonability and compliance of applicable purposes, the reasonability and compliance of indications/applicable conditions, various factors influencing the suitability, the relationship between the factors and the suitability and the like.

The relevant rules for contraindications and their elements may include: the reason of the contraindication exists in the diagnosis scheme, the relationship between various factors possibly influencing the contraindication and the contraindication, guidance and prompt/warning information of related patients/operators/doctors/nurses/pharmacists/caregivers, the results of the contraindication in the above conditions, the grade, degree, sequence and occurrence rate of the corresponding contraindication, the contraindication related evaluation of the patients/operators/doctors/pharmacists/nurses/caregivers, the discovery and remedial measures of the contraindication in the above conditions, and the like.

Relevant rules that require caution/attention and their elements may include: the diagnosis scheme has the relevant contents of reasons requiring caution or attention, relationship between various factors possibly influencing the caution or attention and the caution or attention, guidance/warning information of relevant patients/operators/doctors/nurses/pharmacists/caregivers, the grade, degree, ranking, occurrence probability, danger degree of the caution/attention, possible consequences of the above situations, evaluation of the caution or attention of patients/operators/doctors/pharmacists/nurses/caregivers, discovery of relevant consequences of the above situations, remedial measures and the like.

The rule related to interaction refers to the rule related to the interaction/interaction between the diagnostic methods such as drugs/medical instruments/examinations/operations included in the diagnostic protocol itself, or the interaction/interaction between the diagnostic protocol and other drugs, operations, medical examinations and tests, diet, health products, cosmetics, medical instruments, operations, etc., i.e., if the interaction/interaction exists, the diagnostic protocol should be avoided or carefully selected and care and rescue preparation should be taken during the process.

The relevant rules of interaction and their elements may include: the diagnosis scheme and other medicine/medical apparatus/examination/operation/chemotherapy/radiotherapy/phototherapy/thermotherapy/magnetotherapy/electrotherapy/electromagnetic therapy/phonotherapy/immunotherapy/gene therapy/operation/physiotherapy/rehabilitation/health care/sport/psychology intervention/health care product/health care food/cosmetic/diet and other factors or items exist at the same time/are interacted/interacted with each other, and the diagnosis scheme and relevant medicine/medical apparatus/examination/operation/chemotherapy/radiotherapy/phototherapy/thermotherapy/magnetotherapy/electrotherapy/magnetotherapy/phonotherapy/immunotherapy/gene therapy/operation/physiotherapy/rehabilitation/health care/sport/psychology intervention The effect of the respective site/route/method/time of interaction/dosage/time of interaction of the nutraceutical/cosmetic/diet and the like on the above-mentioned interaction/interaction, and the effect that other factors that may have an effect on the above-mentioned interaction/interaction may have on the interaction.

Other factors that may have an effect on the above interactions/interactions include: patient genetic-related factors, lifestyle-related factors, diet-related factors, disease/treatment history-related factors, family medical history, allergy factors, work/learning/exercise/activity-related factors, environment-related factors, physiological/psychological/learning/sleep/exercise/emotion/metabolism/vision/hearing/intelligence/attention/appetite/immunity/growth/development/memory/fertility etc. state/status/level factors, age-related factors, physiological function-related factors, fertility status-related factors, sexual life status-related factors, and other factors and items that may enhance/reduce/alter the above-mentioned interactions/interactions, and the specific way in which these factors and items affect the relevant interactions/interactions, the disease/treatment history-related factors, family medical history, allergy factors, work/learning/exercise/activity-related factors, environment-related factors, age-related factors, physiological function-related factors, fertility-related factors, sexual life status-related factors, and other factors and items that may enhance/interact with the relevant factors, Influence the result and degree of influence, etc.

The rules relating to interaction may further include: the reasons for the interaction/interaction, the guidance/warning information of the relevant patient/operator/doctor/nurse/pharmacist/caregiver, the consequences of the interaction/interaction, the level, degree, ranking, probability of occurrence, degree of danger/benefit, the evaluation of the relevant interaction/interaction by the patient/operator/doctor/pharmacist/nurse/caregiver, the discovery and remedial action of the interaction/interaction of the above situations, etc. are available in the diagnostic protocol.

The relevant rules and elements of allergy may include physicochemical properties and action principles/mechanisms of drugs/medical instruments/examinations/operations etc. that may cause allergic reactions, and specific elements include: the material comprises components, raw materials, electricity, magnetism, light, heat, radiation, irritation, size, weight, heavy metal, toxicity, smell, shape, specification, package, material, additive, preservative, antifreezing agent, consumable material and relevant information such as relevant concentration, content, strength, valence and the like.

The relevant rules for allergy may also include: the physical constitution, age, sex, height, weight, development related information, birth related information, sexual life related information, genetic related information of the patient, climate/air quality/humidity/season/temperature of the environment, disease/symptom/index/feeling/emotion of the patient, treatment history or treatment plan of the patient, family history/disease history/allergy history/genetic history/regional epidemic history/smoking history of the patient and the like which may possibly have allergy, working condition/learning condition/rest condition/exercise condition/nutritional condition/eating condition/work time/immunity condition of the patient, medicine/operation/chemotherapy/radiotherapy/phototherapy/thermotherapy/magnetotherapy/electrotherapy/magnetotherapy/phonotherapy/immunotherapy/gene therapy and the like The information of concern.

The relevant rules for allergy may also include: the possible manifestations and consequences of allergic reactions under different conditions, the reasons and mechanisms of allergic reactions, the relationship between various factors and allergic reactions that may affect allergic reactions, guidance/warning information of related patients/operators/doctors/nurses/pharmacists/caregivers, the grade, severity, ranking, occurrence probability of allergic reactions, the evaluation of related allergic reactions by patients/operators/doctors/pharmacists/nurses/caregivers, the discovery of related allergic reactions and remedial measures in the above situations, and the like. It is also possible to set the conditions under which the allergy test is to be performed, and if the condition of the patient meets the relevant conditions, the patient needs to go through the allergy test first and the result is negative before the patient can pass the allergy test.

The relevant rules of time and its elements may include: the start time, duration, pause time, break time, progress period, progress frequency, treatment period time, treatment period, treatment interval, treatment course number, onset time, expiration time, end time, etc. of the drug/medical device/examination/surgery, etc. The correlation rules of time may be defined and stored in different time attribute types, and the time-related element attribute types include time element attributes related to natural rhythms such as: year, month, day/night, morning/noon/afternoon/evening/night, season, solar terms, lunar calendar year/month/day, etc.; the time element attributes associated with the time of day are: hours, minutes, hours, etc.; the time element attributes related to the personal work and rest life law are as follows: getting up, before/during/after meal, before sleep; time element attributes associated with a particular condition/symptom/index/psychological state/physiological state/sensation are as follows: body temperature above a certain value, pain, fatigue, vertigo, palpitation, nausea, creatinine clearance above a certain value, blood pressure below a certain value, heart rate above a certain value, emotional depression, feelings of fear, excitement, etc.; treatment-related time element attributes are as follows: one day before a certain examination, 3 hours after a certain operation, when changing a certain medicine, after a certain physical therapy project, etc.; temporal element attributes associated with the age/developmental stage of a patient are as follows: 2 weeks after birth, after eruption of deciduous teeth, after adolescent development, half a year after menopause, climacteric period, etc.; time element attributes associated with a patient's physiological cycle are as follows: first day of menstruation, etc.; time element attributes associated with patient fertility/sexual life are such as: 24 hours after the sexual intercourse of the couple, 3 months before the preparation of pregnancy, 24 weeks of pregnancy, 3 days after the birth, and the like; time element attributes related to patient work/activity/movement/learning are as follows: before sitting on the front of a car, before sitting on a boat, before high-altitude operation, after long-time reading and the like.

The time-related rules may further include: factors which may influence the time and the relationship with the time may also include possible consequences when the diagnosis is not received according to reasonable time in the relevant rules and relevant remedial measures, and may also include interconversion relationship when different time attribute types need to be interconverted between the time and relevant element actual information of the patient diagnosis scheme, and calculation and interconversion relationship between international standard time and time in each time zone.

Relevant rules and elements thereof for developing methods/methods of use may include: the route of acceptance or use, site, time, distance, temperature, environment, condition, equipment/consumable, operation method, operator requirement, protection condition/protection measure, and related precautions of the drug/medical instrument/examination/surgery, etc. The method can also comprise the following steps: the diagnosis protocol may be influenced by and influence the treatment purpose, applicable population, corresponding indication/indication, corresponding health status evaluation item, corresponding environment, performance, dosage, patient drug/medical device/health product/diet/cosmetic/medical examination and examination, patient work/study/exercise related information, patient sexual life/work time/genetic information, etc. Consequences that may arise when a diagnostic protocol is not accepted or developed in the correct manner, and associated remedial actions, may also be included.

Relevant rules for usage and its elements may include: the specification, package, dosage, quantity, intensity, frequency, wavelength, concentration, method, usage range, usage duration, usage area, etc. of the related articles of medicine/medical instrument/examination/operation, etc. include item information that needs to be subjected to unit/data conversion, and may further include: the dosage may be influenced by and influence the purpose, applicable population, corresponding indication/indication, corresponding health status evaluation item, corresponding environment, performance, usage, patient drug/medical device/health product/diet/cosmetic/medical examination and inspection, patient work/study/exercise related information, patient sexual life/work time/genetic information, and the like. The method can also comprise the following steps: single dose/dose, single day or other time unit times/frequency, single day or other time unit dose/dose, total single treatment course, total treatment course times, total dose, and like information. It may also include consequences and associated remedial actions that may occur if a diagnostic protocol is not accepted or developed in the correct amount.

The relevant rules and elements of adverse reactions may include: the relationship between the method/dosage/time/frequency/interval/protective measure of the drug/medical instrument/examination/operation, etc. and the possible adverse reaction, and the relationship between each factor which may affect the adverse reaction and the adverse reaction, may also include: symptoms/index signals/expression/feeling/severity/harm of adverse reactions, treatment of adverse reactions, a method for preventing adverse reactions, remedial measures after adverse reactions occur, and the like.

Relevant rules and their elements for preparation/protection measures may include: physical, chemical, pharmaceutical, food, nutraceutical, rehabilitation, biological, psychological intervention, humanistic, etc. types of preparation/protection/intervention/remedy/recovery related measures taken to avoid or reduce the risk and damage that a diagnostic regimen may present may include the consequences and level of risk thereof that may occur if the preparation/protection measures are not taken according to the relevant rules and the related remedial measures.

The relevant rules for suitability/comfort/compliance and elements thereof may include: comfort, convenience, difficulty, compliance difficulty, beauty, wearing weight, shape, size, volume, floor area, taste, smell, hand, temperature, hardness, irritation, portability, storage convenience, and the like of the medicine/medical instrument/examination/operation, and a method of adjusting suitability/comfort/compliance, including various auxiliary conditions, auxiliary measures, auxiliary methods, auxiliary operations, and the like.

The relevant rules for suitability/comfort/compliance may also include: according to the conditions of the age, the sex, the physical condition, the sensitivity, the tolerance of electrical stimulation/magnetic field/pressure/pain, the taste preference, the motor ability, the physical strength, the work/study/motion/activity/travel rule and characteristic, the work and rest time, the aesthetic requirement, the study ability, the operation ability, the execution ability and the like of the patient, the weight and the combined calculation method of each item related to the suitability/comfort/compliance are set, and the target setting of the suitability/comfort/compliance of the diagnosis scheme of the patient is set. The suitability/comfort/compliance-related rules of (a) may also include a method of prompting the relevant doctor, nurse, pharmacist, patient, caregiver to adjust the corresponding suitability/comfort/compliance when the target setting is not reached.

Relevant rules for medical insurance/welfare and their elements may include: whether the diagnosis plan belongs to the medical welfare/medical insurance or business insurance scope and condition, object, ratio, calculation method, amount and the like, and also can include the limitation of the relevant constraint term hospital/department/doctor/nurse and the like, and also can include information of price, single charge, single daily charge, single treatment course charge, total charge and the like. Whether a diagnostic protocol falls within the medical welfare/medical insurance or business insurance scope and conditions include: people, diagnoses, symptoms, symptom types, operations, examinations, operations, projects, rehabilitation, psychotherapy, physical therapy, health care, nursing, accompanying, areas, medical institutions, departments, doctors, drugstores, examination centers, physical examination centers, treatment centers, rehabilitation centers, dosage of methods, and the like, and combinations thereof. And relevant constraint terms such as violation behaviors, inspection modes, violation punishment measures and the like.

The rules and elements of economic regulation may include: the cost limits of the diagnosis scheme on single cost, single daily cost, single treatment course cost, total cost, time average, per platform/per operation average, per person, per day and per month, the cost limits in different hospitals/departments/doctors/nurses, the cost limits in different diseases/different diagnosis schemes/different projects/patients, and the like, and the economic related indexes of the diagnosis scheme can be preset according to the actual economic capacity and budget of the patient.

Relevant rules and their elements for administration may include: regional related regulations/requirements of diagnostic schemes, hospital-level related regulations/requirements, hospital-property related regulations/requirements, department related regulations/requirements, doctor related regulations/requirements, operator related regulations/requirements, patient related regulations/requirements, disease-type related regulations/requirements, key monitoring related regulations/requirements, extraordinary warning related regulations/requirements, bidding results, price policy related regulations/requirements, day-related regulations/requirements, amount-related regulations/requirements, DRGs (disease-related classification) related regulations/requirements, clinical pathway related regulations/requirements, and the like. Patient-related prescriptions/requirements include: medical insurance, self-service charge, industrial injury, new agriculture and agriculture, dry insurance, chronic diseases, inconvenient movement, old people, disabled people and the like. The amount-related stipulations/requirements include: whether the system meets the related expense limit such as single disease type payment, total amount prepayment, expense proportion control, single variety purchasing/checking amount limit, type purchasing/checking amount limit and the like.

The intelligent diagnostic analysis system of the present invention may also include means to alert the patient/operator/doctor/nurse/pharmacist/caregiver of the various conditions, risks and detection/discovery thereof that may arise when/after the patient receives or develops the relevant diagnostic protocol, as well as the relevant preparation and response methods, and to issue alerts, prompts or initiate remedial actions when conditions are discovered.

The diagnosis scheme is intelligently recommended, various factors such as accuracy, risk, cost and the like need to be balanced, the factors in various aspects can be balanced through preset parameters, and preset coefficients can be modified and changed according to actual conditions to ensure the balance of the factors in various aspects under different conditions. Parameters related to the accuracy, risk and cost of each balance can also be obtained through big data analysis.

The various data acquired by the intelligent diagnosis and analysis system of the present invention may be all data, or may be data of some conditions set as required, for example: data for a certain time period, data of a patient at a certain hospital/department/doctor, etc.

In the intelligent diagnosis and analysis system, the database unit also stores a diagnosis multi-dimensional element attribute dictionary which is used for processing matching/comparison between the acquired information from different sources, different data structures, different descriptions and different data standards and the related information and rules in the database unit. The diagnosis multi-dimensional element attribute dictionary comprises at least one of a standard dictionary, a synonym corresponding dictionary and a fuzzy matching dictionary of diagnosis related element attributes, and comprises data such as synonyms, structures, combinations and mutual corresponding relations of the dimension element attributes related to the items. The matching/comparing may be performed by using the obtained original information to compare with a dictionary corresponding to each item synonym in the diagnostic multidimensional attribute dictionary, or by converting the obtained original information into corresponding standard dictionaries and then comparing with the diagnostic database, or by performing fuzzy matching and comparing between the obtained original information and each dictionary in the diagnostic database, or by a combination of the above methods. The diagnostic multi-dimensional element attribute dictionary may be built separately or may be included in a diagnostic database.

In the invention, besides adopting the diagnostic multidimensional element attribute dictionary for matching, the matching/comparison between the acquired information and the related information and rules in the database unit can be processed by methods such as a voice recognition technology, a semantic recognition technology, translation of different languages, an OCR recognition technology, a virtual reality technology, an augmented reality technology, a gesture recognition technology and the like.

In the present invention, the database unit further stores a patient personal information database including the relevant information of the patient for providing or supplementing the relevant information of the patient at the time of the diagnosis analysis. The patient personal information database comprises the relevant information of the patient, and the content comprises: patient basic information, genetic related information, family health related information such as family medical history, allergy history, regional epidemic history, medication history, surgical history, medical device use history, learning conditions, work conditions, exercise conditions, family conditions, living environment, hobbies, compliance conditions, tolerance conditions, medical insurance conditions, and physiological/psychological/learning/work/physical/sleep/exercise/emotional/metabolic/visual/hearing/mental/attention/diet/immune/growth development/memory/fertility conditions, and time of rest.

In the invention, the database unit further stores a medical personnel personal information database, and the medical personnel personal information database comprises the relevant information of the medical personnel and is used for providing or supplementing the relevant information of the medical personnel during diagnosis and analysis. The medical personnel personal information database comprises the related information of the medical personnel, and the content comprises the following components: the medical staff's study, profession, specialty, title, job title, practice hospital, department, and the related habits of prescribing medical advice, including related experience, medical advice writing habits, general medical advice rules, etc.

The data acquisition method of the patient personal information database and the medical personnel personal information database comprises the steps of acquiring or accessing from other information systems, equipment or databases and analyzing, or manually inputting, or continuously acquiring and analyzing new data in the using process of relevant information of the databases, or the combination of the methods.

In the present invention, the source of the information related to the patient can be a patient personal information database, health file, family or family member health record, medical order, medical record, medical calendar, prescription, electronic medical record, medical institution information system, pharmacy/medical facility information system, medical record, treatment record, assessment report, consultation record, survey record, work record/plan, diet record/plan, shopping record/plan, medication record/plan, treatment record/plan, exercise record/plan, work record/plan, learning record/plan, rehabilitation record/plan, health record/plan, examination/examination order, surgery record/record, health management plan, billing order, clinical treatment path, examination/examination result, health management plan, medical record/examination order, health record/plan, health management record/plan, health record/examination order, health record/examination result, health record/examination order, health management plan, health care order, health care path, medical treatment path, examination/examination result, health record/examination result, health management plan, health management record/examination result, health management record, health, The operation setting/record and the gene detection result can be obtained from the use/prescription/recommendation record of the patient/doctor/nurse, or can be provided by various wearable devices, sensors, electronic devices, an electronic positioning system, a weather forecast system, an electronic temperature/humidity/air pressure detection device, an intelligent sound box, an intelligent home system, an intelligent monitoring/monitoring system, intelligent glasses, an intelligent closestool, an intelligent ground, an intelligent scale, an intelligent detection/analysis device, an electronic infusion system, an operation robot, face recognition analysis, fingerprint recognition, voice recognition, gait recognition, a positioning system, a social platform and other devices or systems, or can be obtained by analyzing the information of the life, study, work, movement, trip, social interaction, shopping, diet, work, entertainment and the like of the patient through big data, the information can also be analyzed by the patient's race/family/region/age/marital/birth, etc. The missing information may also be provided or refined by the patient/doctor/nurse/caregiver, or the information with high relevance may actively prompt the patient/doctor/nurse/caregiver to observe, monitor, check, query, analyze, confirm, record whether the relevant condition occurs or obtain the relevant index/performance/feeling/symptom/physiological change, the relevance is set or analyzed by data, the relevant elements are ranked or ordered according to the importance of the diagnosis scheme rationality and compliance in the aspects of effectiveness, safety, economy, suitability/comfort/compliance, etc., and the information with high importance may be set as the information that must be refined or cannot be processed in the next step. Assessment reports include physiological, psychological, economic, credit, athletic ability, and the like. The intelligent detection/analysis device includes: odor, image, sound, pulse condition, X-ray film, CT, nuclear magnetic, ultrasonic examination, brain wave, mass spectrum analyzer, tongue analysis, fundus examination, gastroscope, enteroscope, catheter, minimally invasive scope, heart rate, blood oxygen, blood pressure, blood sugar, blood fat, body temperature, blood examination, urine examination, stool examination, pulse measurement/analysis equipment, etc.

In the invention, each item of recommendation, evaluation, report and other output information of the intelligent diagnosis and analysis system can be manually completed by professional personnel according to the diagnosis database and each item of data, or manually completed under the support of the system, or automatically completed by artificial intelligence, or completed by combining a system/artificial intelligence completion part with a manual completion part. The form of the application/output of the related diagnosis and analysis result can be realized by functions of reminding, informing, reporting, system authority limit, system flow limit, control of related systems/equipment/files/authorities and the like; or providing related interfaces to be realized by being in butt joint with other management systems; or an application that provides the recommendation and manually implements the relevant recommendation by the user.

In the invention, the identity recognition, confirmation, login and electronic signature of patients, medical personnel and related roles of the intelligent diagnosis and analysis system, and the storage, transmission and application of personal information, medical advice information and various analysis results can be encrypted by various methods, so that the related identity/authority can be prevented from being stolen or information is prevented from being leaked. Wherein the encryption algorithm comprises a symmetric encryption algorithm and/or an asymmetric encryption algorithm, such as: the large integer decomposition problem encryption algorithm, the discrete logarithm problem encryption algorithm, the elliptic curve encryption algorithm, specifically, the block chain technique, etc., the encryption hardware may adopt a secret key, a dongle, an encrypted hard disk, etc., and may be encrypted in combination with user equipment hardware, a network address, etc., or may be encrypted in combination with each other.

In the invention, the data transmission mode of the intelligent diagnosis and analysis system can be a data line mode, a wired network, a wireless transmission mode, a radio frequency identification mode, a magnetic card read-write mode, a mobile hard disk mode, an NFC mode, a bar code mode, a two-dimensional code mode and the like. The wireless transmission mode comprises: infrared, bluetooth, wifi, microwave, visible light wave, telecommunication wireless network, ultrasonic/sound wave, radio, etc.

In the invention, the intelligent diagnosis and analysis system can be used by a single machine, or can be used by users through access type external hardware such as a mobile hard disk, a box, a card and the like, or can be installed on a local server to support the use of the local users, or can be installed on a private cloud server to support the use of the private cloud users, or can be installed on the Internet to provide services for Internet users.

The intelligent diagnosis and analysis system can comprehensively analyze, remind and recommend the whole process from the safety, effectiveness, economy and suitability of diagnosis, can effectively avoid the problem of unreasonable and untimely diagnosis caused by insufficient professional skills of medical personnel, individual difference of patients, human errors and the like, and ensures that the patients can reasonably diagnose and treat.

For example: each level of health administration department can establish a plurality of versions of intelligent diagnosis and analysis systems in the same or different areas according to the actual conditions of the area, and when different medical institutions, clinics, health hospitals, health stations, departments, doctors, nurses, inspectors and the like in the jurisdictions carry out diagnosis, the intelligent diagnosis and analysis systems carry out analysis on the diagnosis, and can recommend, audit and comment on diagnosis conclusions and diagnosis schemes. The recommendation can be performed by a system installed locally or a system installed in an Internet/local area network server, can be automatically completed by the system, and can also be performed by outputting a formal recommendation result after a relevant result is confirmed/adjusted by a recommendation post after the system completes pre-recommendation. The diagnosis and analysis result can be used for managing the diagnosis process of the patient, can also be used as the basis for adjusting medical orders, and can also be used for assessing the medical quality/work performance/professional ability assessment/vogue assessment/service quality assessment/benefit accounting and the like of different medical institutions, departments, doctors, nurses, pharmacists, inspectors and the like.

For another example: a data service center can be established, and the intelligent diagnosis analysis system is used for providing diagnosis conclusion and recommendation service of diagnosis schemes for users such as medical institutions, clinics, health hospitals, health stations, medical insurance institutions, insurance companies, doctors, pharmacists, nurses, inspectors, patients, caregivers and the like. The data service center can assist the user to generate diagnosis databases of different versions which are regulated and configured individually according to the characteristics and requirements of the user such as attributes, scale, service, region, economic condition, management system, use habit and the like, can customize different data transmission, storage, output and application processes/modes/formats according to different user service processes, and can be used for docking different systems, networks, equipment and mechanisms.

A second embodiment of the present invention is seen in figure 2. FIG. 2 is a flow chart of a method of using an intelligent diagnostic and analysis system of the present invention. As shown, the method of using the intelligent diagnostic and analysis system includes:

step 1, establishing a diagnosis database, wherein the diagnosis database comprises the relation between disease information and diseases;

step 2, acquiring disease information of a patient;

step 3, setting a diagnosis and analysis model, wherein the diagnosis and analysis model is used for giving a diagnosis conclusion and comprises at least one parameter of possibility/probability, severity, urgency, treatment scheme difference and cost of diseases;

and 4, giving a diagnosis analysis result according to the disease information of the patient, the relation between the disease information and the disease and the diagnosis analysis model.

The use method of the intelligent diagnosis and analysis system can also comprise a recommended diagnosis scheme, and the recommended diagnosis scheme comprises the following steps:

step 101, analyzing whether a diagnosis can be made based on existing patient disease information? If yes, executing step 103, if no, executing step 102;

102, recommending a diagnosis scheme suitable for a patient according to the existing patient disease information, acquiring more patient disease information through the diagnosis scheme, and returning to the step 101;

and 103, obtaining a diagnosis conclusion and finishing the recommendation of the diagnosis scheme.

The application method of the intelligent diagnosis and analysis system of the present invention corresponds to the technical features of the intelligent diagnosis and analysis system of the present invention one to one, and reference may be made to the description of the intelligent diagnosis and analysis system, which is not repeated herein.

In summary, the intelligent diagnosis and analysis system and the using method thereof of the present invention include: the device comprises a database unit, an information acquisition unit, a model unit and an analysis unit. The use method of the intelligent diagnosis and analysis system comprises the steps of establishing a diagnosis database, obtaining disease information of a patient, setting a diagnosis and analysis model, and giving a diagnosis and analysis result according to the disease information of the patient, the relation between the disease information and the disease and the diagnosis and analysis model. According to the intelligent diagnosis and analysis system and the use method thereof, the aspects of safety, effectiveness, economy, suitability and the like in the diagnosis process of the patient are comprehensively analyzed and recommended in the whole process on the basis of technical data such as diagnosis and treatment specifications, the phenomena that the diagnosis conclusion is inaccurate and the diagnosis scheme is unreasonable due to the fact that medical staff cannot know the specific content of disease diagnosis sufficiently, or the individual information of the patient is not mastered sufficiently, or human errors occur in the actual diagnosis process can be avoided, so that the medical staff and the patient can be helped to quickly and accurately obtain scientific diagnosis paths and diagnosis conclusions, and the accuracy and timeliness of diagnosis are effectively improved.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (11)

1. An intelligent diagnostic analysis system, the system comprising:

a database unit for storing a diagnosis database including a relation of disease information and a disease;

an information acquisition unit for acquiring disease information of a patient;

a model unit for setting a diagnosis analysis model for giving a diagnosis conclusion including at least one parameter of possibility/probability of a disease, severity, urgency, difference of treatment protocol, cost;

and the analysis unit is used for giving a diagnosis analysis result according to the patient disease information, the relationship between the disease information and the disease and the diagnosis analysis model.

2. The intelligent diagnostic analysis system of claim 1, wherein the diagnostic analysis results comprise: judging whether a diagnosis conclusion can be obtained according to the existing information, evaluating whether the existing diagnosis conclusion is correct, recommending the diagnosis conclusion, and recommending at least one of diagnosis schemes for continuing diagnosis.

3. The intelligent diagnostic and analysis system of claim 1, wherein: the analysis unit respectively sets corresponding levels/scores according to different analysis results of at least one analysis item of possibility/probability, severity, urgency, treatment scheme difference and treatment cost of patients suffering from different diseases under different disease information/patient information conditions, and can calculate comprehensive levels/scores of different diagnosis conclusions under the disease information/patient information conditions according to the levels/scores corresponding to the diagnosis conclusions obtained through diagnosis analysis in each analysis item and a set diagnosis analysis model so as to facilitate the analysis unit to give the diagnosis analysis results.

4. The intelligent diagnostic and analysis system of claim 1, wherein: the intelligent diagnosis and analysis system also comprises a step of evaluating the original diagnosis and analysis result or carrying out the diagnosis and analysis again to obtain a new diagnosis and analysis result according to new patient disease information obtained in the treatment process or the treatment result or according to the actual treatment effect of the diagnosis conclusion.

5. The intelligent diagnostic and analysis system of claim 1, wherein: the diagnosis database also comprises the relation between the diseases and the diagnosis schemes, and the analysis unit analyzes the possible disease range of the patient according to the disease information of the patient and the relation between the disease information and the diseases, and then obtains a diagnosis scheme recommendation list according to the possible disease range of the patient and the relation between the diseases and the diagnosis schemes.

6. The intelligent diagnostic and analysis system of claim 5, wherein: the diagnosis database also comprises relevant rules of reasonability and compliance of the diagnosis scheme, and the analysis unit optimizes the recommendation list of the diagnosis scheme according to the relevant rules of reasonability and compliance of the diagnosis scheme.

7. The intelligent diagnostic and analysis system of claim 6, wherein: relevant rules for rationality and compliance of the diagnostic protocol include: at least one of rules related to applicability, rules related to contraindications, rules related to need of caution/attention, rules related to interaction, rules related to allergy, rules related to time, rules related to method of development/method of use, rules related to dosage, rules related to adverse reaction, rules related to preparation/protective measures, rules related to suitability/comfort/compliance, rules related to medical insurance/welfare, rules related to economic regulation, and rules related to administrative management.

8. The intelligent diagnostic analysis system of any one of claims 1-7, wherein: the database unit also stores a patient personal information database which comprises the relevant information of the patient and is used for providing or supplementing the relevant information of the patient in the diagnosis analysis.

9. The intelligent diagnostic analysis system of any one of claims 1-7, wherein: the database unit also stores a diagnostic multi-dimensional element attribute dictionary for processing matching/comparison of the acquired information with the related information and rules in the database unit.

10. A method of using the intelligent diagnostic analysis system of any one of claims 1-9, the method comprising:

step 1, establishing a diagnosis database, wherein the diagnosis database comprises the relation between disease information and diseases;

step 2, acquiring disease information of a patient;

step 3, setting a diagnosis and analysis model, wherein the diagnosis and analysis model is used for giving a diagnosis conclusion and comprises at least one parameter of possibility/probability, severity, urgency, treatment scheme difference and cost of diseases;

and 4, giving a diagnosis analysis result according to the disease information of the patient, the relation between the disease information and the disease and the diagnosis analysis model.

11. The method of claim 10, further comprising recommending a diagnostic protocol, the recommending a diagnostic protocol comprising the steps of:

step 101, analyzing whether a diagnosis can be made based on existing patient disease information? If yes, executing step 103, if no, executing step 102;

102, recommending a diagnosis scheme suitable for a patient according to the existing patient disease information, acquiring more patient disease information through the diagnosis scheme, and returning to the step 101;

and 103, obtaining a diagnosis conclusion and finishing the recommendation of the diagnosis scheme.

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