Construction method and equipment of medical service system for cerebral apoplexy prediction and analysis

Abstract

The invention discloses a construction method and equipment of a medical service system for cerebral apoplexy prediction and analysis. The equipment comprises wearable hardware detection equipment, an intelligent terminal module, an intelligent AI module and a medical service module. Through the combination of the intelligent AI module and other modules, mass data can be integrated and analyzed, high-risk groups can be identified more accurately through deep learning of body health data of different individuals, different individual cerebral apoplexy prediction services are provided, and corresponding cerebral apoplexy prevention medical service schemes are formulated. Therefore, the medical service capability of early prediction and early prevention of the cerebral apoplexy is improved, the incidence rate and the recurrence rate of the cerebral apoplexy are more effectively reduced, the workload of medical care for cerebral apoplexy diseases can be greatly reduced through the intelligent AI module, and the accuracy rate of prediction of the cerebral apoplexy diseases is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of stroke medical services, and in particular to a method and device for constructing a medical service system for stroke prediction and analysis. Background Art

[0002] Stroke, commonly known as stroke, is divided into two types: ischemic stroke and hemorrhagic stroke. It is a disease caused by various reasons that damage cerebral blood vessels and cause focal or global brain tissue damage. Stroke is one of the main causes of death and disability worldwide.

[0003] The World Stroke Organization reminds that among people over the age of 25, one in four people in the world will be at risk of stroke in their lifetime. It is worth noting that the incidence of stroke is also tending to be younger. The "China Stroke Prevention and Treatment Report (2023)" shows that the current number of stroke patients aged 40 and above in my country has reached 12.42 million. The recurrence rate of acute stroke patients in China within one year is as high as 17.7%, and the cumulative recurrence rate in five years exceeds 30%, of which about 25% of patients will die from a secondary stroke. In my country, men over 45 years old and women over 55 years old with hypertension, diabetes, hyperlipidemia, coronary heart disease, family history of stroke, long-term inactivity or lack of physical activity, and certain bad habits and lifestyles are a large group of more than 200 million people.

[0004] At present, the diagnosis and treatment of stroke are all done by medical examination, diagnosis and treatment after the patient has symptoms. Due to the difficulty in diagnosis and treatment, irreversibility of the disease, high recurrence rate, high disability rate and mortality rate of stroke, stroke brings huge economic and mental burden to patients and their families. In addition, the prediction of stroke is greatly influenced by the subjective influence of medical staff, and the workload of detection is large, so it is easy to miss or misdetect, which affects the treatment of symptoms.

[0005] Therefore, the prior art still needs to be improved and enhanced. Summary of the invention

[0006] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a method and equipment for constructing a medical service system for stroke prediction and analysis, aiming to solve the problem that the prediction of stroke in the prior art is greatly influenced by the subjectivity of medical staff, the detection workload is large, and it is easy to miss or misdetect, which affects the treatment of the disease.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, a method for constructing a medical service system for stroke prediction and analysis includes: S1. Build a stroke database; S2. Establish an evaluation index system for predicting and analyzing individual differences in stroke; S3. Develop hardware equipment for health checks suitable for users’ home use; S4. Establish a resource guarantee mechanism for stroke prevention medical service measures; S5. Build a stroke intelligent medical service platform that connects users and medical service resources; S6. Develop software systems based on network and hardware systems.

[0008] Furthermore, the step S1 includes: By inputting data from the smart terminal module and the detection data from the wearable hardware detection equipment, the body's biochemical indicators, physiological indicators, surface indicators and functional indicators are stored in the stroke database built in the background of the stroke medical ecosystem; by collecting and analyzing various body indicator data of users in real time, a mapping and logical relationship between individuals and stroke influencing factors is established, so as to predict individual stroke and provide corresponding medical prevention measures.

[0009] Furthermore, the step S2 comprises: Based on the individual body index data in the stroke database and the real-time detection data of wearable hardware detection devices, a mathematical model of intelligent stroke prediction and analysis is constructed to establish a dynamic and individually different stroke prediction and analysis evaluation index system suitable for different users, make a qualitative evaluation of stroke prediction and analysis, and clarify the classification characteristics.

[0010] Further, the step S4 includes: Based on the individual differences in health care needs of users, a medical resource guarantee mechanism is established to guarantee the medical resources required for stroke prevention for ordinary users, an operating mechanism is established to absorb different medical service resources and expand the scope of medical services, and while ensuring that system users can receive medical services in a timely manner and meet their health needs, a reasonable allocation and scheduling of medical service resources is established.

[0011] Furthermore, the step S5 comprises: The intelligent stroke prevention service platform is located at the core position connecting users with different stroke medical service resources. It has the medical service functions of providing individual differences in stroke prediction and prevention, and intelligent configuration of medical resources for ordinary users. On this platform, a stroke prediction mathematical model is built based on Markov Chain, combined with the data in the stroke database, and mapped and matched with stroke medical service resources through intelligent data analysis. According to the physical health data provided by the user in real time through hardware detection equipment, it can predict and analyze the results of stroke and meet the actual use needs of scheduling and matching between users and stroke medical service resources in real time.

[0012] Furthermore, when establishing a dynamic stroke prediction analysis and evaluation index system suitable for different users and with individual differences, a stroke intelligent prediction mathematical model based on Markov Chain is established based on the four main factors for predicting and judging the development of stroke; Among them, the four main factors include blood lipids and liver function biochemical indicators obtained from blood and secretion body fluid examinations; heart rate, body temperature, blood pressure, carotid artery pulsation, and sleep physiological indicators; height, weight, facial expression, skin appearance, hair appearance, appetite, and head sensation body surface indicators; physical exercise level, memory, perception ability, drinking, smoking, and medical history physical function indicators.

[0013] Furthermore, the establishment of a mathematical model for intelligent prediction of stroke based on Markov Chain includes: First, construct a vector set of the probability of occurrence of indicators required to predict stroke: Will Defined as 4 indicator vector sets respectively, construct the Markov chain transfer chain probability matrix of stroke judgment factors : ; in, m=i,j,h,kn=i,j,h,k; According to the properties of Markov chain probability distribution, the transfer matrix is ​​a positive definite matrix, and the sum of the probabilities of each row is equal to 1; ; Secondly, determine the probability of individual stroke prediction and judgment index vector : It is necessary to construct a 4th-order bias weight matrix, combine the Markov Chain with the neural network intelligent learning structure, and use parameters and activation functions to fit the true functional relationship between stroke characteristics and prediction and judgment as closely as possible; the constructed bias weight coefficient is ,in m≠n,m,n=I,j,h,k ; Then, the probability of multi-factor judgment index of individual difference stroke was constructed; According to gender, subjective indicators of age, BMI, heart rate, blood pressure, carotid pulse, sleep, physical exercise level, head feeling, memory, perception, drinking, smoking and objectively detectable current moment indicators are defined as , is the previous value of the indicator at the current moment, is the mean value of the indicator at the current moment; For statistics and and Statistics of different relationships: ; ; The current moment indicator Contribution rate of indicators to stroke incidence; ; Finally, the stroke risk probability and response measures are determined based on the risk matrix: according to The probability distribution divides the stroke risk level into five intervals: extreme risk above 90%, high risk 70%-90%, risk 40%-70%, lower risk 10%-40%, and low risk below 10%; For different indicators The percentage of the number to the total number of indicators is defined as the individual contribution ratio of stroke: ; Various subjective and objective indicators such as age, BMI, heart rate, blood pressure, carotid pulse, sleep, physical exercise level, head feeling, memory, perception, drinking, and smoking are set as spatial percentage vectors; Then by physical indicators , Individual contribution ratio of stroke % and the probability of multi-factor judgment index of stroke In the set of spatial vectors formed, different coping measures taken by different individuals to stroke are determined.

[0014] In a second aspect, a medical service device established by a method for constructing a medical service system for stroke prediction and analysis includes: Wearable hardware testing equipment; Intelligent terminal module, bidirectionally connected to wearable hardware detection equipment; An intelligent AI module is bidirectionally connected to the intelligent terminal module. The intelligent AI module includes an intelligent AI data analysis module and an intelligent AI analysis model for health data. The intelligent AI analysis model for health data is used to receive data information of different medical resources. The intelligent AI data analysis module is used to receive the user's individual health data integrated by the intelligent terminal module, and form a mapping and logical deduction with the intelligent AI analysis model for health data, and finally feed back the user's health data analysis results and the optimal medical service plan; The medical service module is bidirectionally connected to the intelligent AI module.

[0015] The technical solution adopted by the present invention has the following beneficial effects: In the present invention, through the intelligent AI module and the medical service module, massive data can be integrated and analyzed. It can also more accurately identify high-risk groups through deep learning of the physical health data of individuals with differences, provide differentiated individualized stroke prediction services and formulate corresponding stroke prevention medical service plans, thereby improving the medical service capabilities of early prediction and early prevention of stroke, more effectively reducing the incidence and recurrence rate of stroke, and the intelligent AI module can greatly reduce the workload of medical staff for stroke symptoms and improve the accuracy of stroke symptom prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic diagram of the structure of a medical service system device for stroke prediction and analysis provided by the present invention; Figure 2 A comparison chart of individual stroke risk probability and coping measures for a method for constructing a medical service system for stroke prediction and analysis provided by the present invention; Figure 3 A schematic diagram of a data transmission flow between hardware systems of a medical service system device for stroke prediction and analysis provided by the present invention; Figure 4 A schematic diagram of a method for constructing a medical service system for stroke prediction and analysis provided by the present invention; Figure 5 The present invention provides a user operation process of a medical service system device for stroke prediction and analysis. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] First, in this embodiment, a device for a medical service system for stroke prediction and analysis is mainly composed of four parts: a wearable hardware detection device, an intelligent terminal module, an intelligent AI module, and a medical service module. Figure 1 and Figure 3 As shown, where: Wearable hardware detection equipment is deployed at the user's location to detect the user's individual health data in real time. This system is an instrument that integrates carotid artery detection and radial artery detection. It is a convenient health data detection device for home use. It can detect and transmit the user's relevant body detection data in real time, providing the most direct basic data for the user's stroke prediction and analysis. The intelligent terminal module is wirelessly connected to the wearable hardware detection device to receive and integrate the user's individual health data. The hardware is mainly based on terminal input and output devices such as mobile phones or computers. This type of hardware system is the carrier of the software system and can be used as both input and output devices. For example, a mobile terminal with a special APP installed can input user data information for data model analysis and judgment, and can also be used as an output device to receive or actively query data information such as data analysis results; As for the software, it is the user's mobile terminal App. The user's mobile terminal App receives the data of "wearable hardware detection device" and uploads the data of "wearable hardware detection device", "objective body data" and "image data" to the "background data intelligent AI analysis and processing server". At the same time, it also receives information data from the "background data intelligent AI analysis and processing server", which belongs to the software module.

[0019] The intelligent AI module includes an intelligent AI data analysis module and an intelligent AI analysis model for big health data. The intelligent AI analysis model for big health data is used to receive data information of different medical resources. The intelligent AI data analysis module is used to receive individual physical health data of users integrated by the intelligent terminal module, and form a mapping and logical deduction with the intelligent AI analysis model for big health data, and finally feed back the physical health data analysis results and the optimal medical service plan to the user.

[0020] The hardware of the intelligent AI module is the background data intelligent AI analysis and processing server; this system is composed of different servers such as data storage and data analysis. This part is the core part of the system of this project, mainly composed of two modules: "intelligent AI data analysis module" and "intelligent AI analysis model of physical health data". After the "intelligent AI data analysis module" receives data from the user side, it maps and logically deduce with the internal modules of the "intelligent AI analysis model of physical health data", and finally feeds back the user's physical health data analysis results and the optimal medical service plan. At the same time, the "intelligent AI analysis model of physical health data" module receives data information from different medical resources. While increasing the medical service database, it can also increase personalized optimal medical service plans. The "intelligent AI data analysis module" will feed back data information such as user data analysis results and corresponding medical service plans to medical service resources.

[0021] The medical service module has a medical service database, which integrates medical data, drugs, and rehabilitation training data information about stroke, and feeds the data information back to the intelligent AI module. This module belongs to the information data integration module, which integrates medical service data such as health care drugs, rehabilitation training services, and physical examination health services, and maps and matches the data based on the intelligent analysis of the "background data intelligent AI analysis and processing server" to provide users with the best medical services. The construction of medical service end system software can enable different medical resource data to be uploaded to the "background data intelligent AI analysis and processing server", and can also provide corresponding medical services to end users based on the data information fed back by the "background data intelligent AI analysis and processing server".

[0022] The second aspect is a medical service method of a medical service system for stroke prediction and analysis, such as Figure 4 As shown, including: S1. Constructing a stroke database. Constructing a stroke database is the basis for constructing the medical service system in the present invention, and is a key part of providing corresponding medical service measures for individual differences. First, the database stores data information and medical service resource information of different users. By deeply mining and analyzing the data of a large number of users, through the APP user input data and hardware equipment detection data, the body biochemical indicators, body physiological indicators, body surface indicators and body function indicator data can be stored in the stroke database constructed in the background of the stroke medical ecosystem. By collecting and analyzing various types of user's physical indicator data in real time, establishing the mapping and logical relationship between individuals and stroke influencing factors, it is possible to predict individual stroke and provide corresponding medical prevention measures with individual differences.

[0023] S2. Establish an evaluation index system for predicting and analyzing individual differences in stroke; Based on the individual body index data in the stroke database and the real-time detection data of the hardware detection equipment, through the construction of the intelligent stroke prediction and analysis mathematical model, a dynamic and individualized stroke prediction and analysis evaluation index system suitable for different users is established, which can make a qualitative evaluation of the prediction and analysis of stroke and clarify the classification characteristics. At the same time, in terms of quantitative evaluation, it can provide personalized medical service measures required for stroke prevention.

[0024] Specifically, in this embodiment, existing studies have shown that the main factors that can predict and judge the development of stroke can be divided into four indicators: biochemical indicators such as blood lipids and liver function obtained from examinations of body fluids such as blood and secretions; physiological indicators such as heart rate, body temperature, blood pressure, carotid artery pulsation, and sleep; surface indicators such as height, weight, facial expression, skin appearance, hair appearance, appetite, and head sensation; and functional indicators such as physical exercise level, memory, perception, drinking, smoking, and medical history.

[0025] Since these four indicators have a certain proportion of correlation with each other, they have mapping and logical relationships, and the probability distribution of the future state of each indicator depends only on the current state. In particular, the medical service system constructed in the present invention is a home-based medical service, and the body biochemical indicators cannot be obtained in real time, and can only be predicted and estimated through other indicators.

[0026] Therefore, in the present invention, a mathematical model for predicting stroke based on Markov Chain is designed. When the intelligent AI module analyzes the user's individual physical health data, based on the four main factors for predicting and judging the development of stroke, a mathematical model for intelligent prediction of stroke based on Markov Chain is established to provide risk warnings for the user's stroke symptoms and feedback on countermeasures.

[0027] The establishment of a mathematical model for intelligent stroke prediction based on Markov Chain specifically includes: First, construct a vector set of the probability of occurrence of indicators required to predict stroke: Will Defined as 4 indicator vector sets respectively, construct the Markov chain transfer chain probability matrix of stroke judgment factors : in, m=i,j,h,kn=i,j,h,k According to the properties of Markov chain probability distribution, the transfer matrix is ​​a positive definite matrix, and the sum of the probabilities of each row is equal to 1; ; Secondly, determine the probability of individual stroke prediction and judgment index vector : In fact, the probability of the indicator vector required for stroke prediction and judgment constructed by using Markov Chain alone cannot eliminate individual differences. Therefore, it is necessary to construct a 4th-order bias weight matrix, combine Markov Chain with the neural network intelligent learning structure, and use parameters and activation functions to infinitely fit the true functional relationship between stroke characteristics and prediction and judgment; the constructed bias weight coefficient is ,in m≠n,m,n=I,j,h,k ; Then, the probability of multi-factor judgment index of individual difference stroke was constructed; According to gender, subjective indicators such as age, BMI, heart rate, blood pressure, carotid pulse, sleep, physical exercise level, head feeling, memory, perception, drinking, smoking and objectively detectable current moment indicators are defined as , is the previous value of the indicator at the current moment, is the mean value of the indicator at the current moment. For statistics and and Statistics of different relationships: The current moment indicator Contribution rate of indicators to stroke incidence; Finally, the stroke risk probability and response measures are determined based on the risk matrix: according to The probability distribution divides the stroke risk level into five intervals: extreme risk (>90%), high risk (70%-90%), risky (40%-70%), relatively low risk (10%-40%), and low risk (<10%); For different indicators The percentage of the number to the total number of indicators is defined as the individual contribution ratio of stroke: Various subjective and objective indicators such as age, BMI, heart rate, blood pressure, carotid pulse, sleep, physical exercise level, head feeling, memory, perception, drinking, smoking, etc. are set as spatial percentage vectors; Then by physical indicators , Individual contribution ratio of stroke % and the probability of multi-factor judgment index of stroke In the spatial vector set formed by , we can determine the different coping measures taken by different individuals to deal with stroke. Figure 2 shown.

[0028] S3. Develop hardware equipment for health checks suitable for users’ home use; In order to complete the basic physical health data required for stroke detection at home, it is necessary to develop a carotid and radial artery data indicator detection device that is simple to operate, compact, and easy to use, which can obtain carotid artery pulsation frequency and strength, as well as heart rate, blood pressure, sleep, blood oxygen content, respiratory rate and other physical indicator data. These real-time collected physical data can be used for comprehensive analysis with the stroke database, and through individual difference stroke prediction analysis, the stroke prediction analysis results can be finally obtained.

[0029] S4. Establish a resource guarantee mechanism for stroke prevention medical service measures; The present invention is a medical service system developed for the prevention of stroke in the general population, and its purpose is to reduce the risk of stroke and the incidence of stroke through effective preventive measures. Therefore, the medical service system of the present invention establishes a medical resource guarantee mechanism that can guarantee the medical resources required for stroke prevention for general users according to the individual differences in health care needs of users, and can absorb different medical service resources and expand the operating mechanism of medical service scope. While ensuring that system users can obtain medical services in a timely manner and meet their health needs, it can also realize the reasonable allocation and scheduling of medical service resources.

[0030] S5. Build a stroke intelligent medical service platform that connects users and medical service resources; The stroke intelligent prevention service platform is located at the core of connecting users with different stroke medical service resources. It has the functions of providing individual differences in stroke prediction and prevention, intelligent configuration of medical resources and other medical services for ordinary users. On this platform, by building a stroke prediction mathematical model based on Markov Chain, combining it with the data in the stroke database, and mapping and matching it with stroke medical service resources through intelligent data analysis, it can predict and analyze the results of stroke and meet the actual needs of scheduling and matching between users and stroke medical service resources in real time according to the physical health data provided by users through hardware detection equipment in real time.

[0031] S6. Develop software systems based on network and hardware systems; An embedded software system is developed based on the physical detection hardware equipment, the purpose of which is to enable the carotid artery detection data and the radial artery detection data to be coordinated and consistent. At the same time, according to the actual needs of data input, data transmission, data storage, data analysis and data display required for stroke prediction, a network software system is constructed to realize the functions of data collection, transmission and reception and processing between mobile phone APP and hardware equipment. In view of the service requirements of medical service resources required for stroke prevention measures, the present invention designs the operation requirements of different functional tasks in the software system of the developed platform part, which can ensure the actual functional requirements of data transmission, storage, analysis and display between users, medical service resources and system platforms.

[0032] The use process of the stroke intelligent prediction and analysis medical service system is as follows Figure 5 As shown, users can obtain stroke prediction and analysis, as well as individual medical service measures provided by the intelligent medical service system through the front-end program system on the mobile phone APP.

[0033] (1) First, 1. the user connects to 3. the hardware detection device through 2. the mobile phone APP, 1. the user controls 3. the hardware detection device through 2. the mobile phone APP, and 3. the hardware detection device automatically transmits the detection data to 2. the mobile phone APP for storage and uploading. 1. the user can view the body data detected by 3. the hardware detection device on 2. the mobile phone APP.

[0034] (2) Next, the detection data of 3. hardware detection equipment stored in 2. mobile phone APP can be automatically uploaded to 4. intelligent medical service platform; 1. users can also use 2. mobile phone APP to manually input data information and upload it to 4. intelligent medical service platform. This data information is 1. the user's personal subjective and objective physical data, including age, gender, height, weight, personal feeling, physical exercise, etc.

[0035] (3) Next, 4. the intelligent medical service platform stores, analyzes and processes 2. the data uploaded by the mobile phone APP to obtain 1. the user's stroke prediction and analysis data information, and at the same time, determines stroke medical measures with individual differences.

[0036] (4) Next, 4. the intelligent medical service platform will send the stroke prediction analysis data and stroke prevention medical measures to 2. the mobile phone APP, and 1. the user will obtain feedback data information through 2. the mobile phone APP.

[0037] (5) At the same time, 4. the intelligent medical service platform will send the resource scheduling information required to determine the medical measures for stroke with individual differences to 5. the medical service resources.

[0038] (5) Finally, 5. the medical service resources will feed back the resource data information to 4. the intelligent medical service platform, which will then send 5. the medical service resource scheduling information to 2. the mobile app, and 1. the user will use 2. the mobile app to determine whether he or she needs the medical services provided by 5. the medical service resources.

[0039] From then on, the complete use process of the stroke intelligent prediction and analysis medical service system has been completed.

[0040] In the present invention, through the intelligent AI module and the medical service module, massive data can be integrated and analyzed. It can also more accurately identify high-risk groups through deep learning of the physical health data of individuals with differences, provide differentiated individualized stroke prediction services and formulate corresponding stroke prevention medical service plans, thereby improving the medical service capabilities of early prediction and early prevention of stroke, more effectively reducing the incidence and recurrence rate of stroke, and the intelligent AI module can greatly reduce the workload of medical staff for stroke symptoms and improve the accuracy of stroke symptom prediction.

[0041] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the schemes disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the claims.

Claims

1. A method for constructing a medical service system for stroke prediction and analysis, characterized in that: include: S1. Build a stroke database; S2. Establish an evaluation index system for predicting and analyzing individual differences in stroke; S3. Develop hardware equipment for health checks suitable for users’ home use; S4. Establish a resource guarantee mechanism for stroke prevention medical service measures; S5. Build a stroke intelligent medical service platform that connects users and medical service resources; S6. Develop software systems based on network and hardware systems.

2. The method for constructing a medical service system for stroke prediction and analysis according to claim 1, characterized in that: The step S1 comprises: By inputting data from the smart terminal module and the detection data from the wearable hardware detection equipment, the body's biochemical indicators, physiological indicators, surface indicators and functional indicators are stored in the stroke database built in the background of the stroke medical ecosystem; by collecting and analyzing various body indicator data of users in real time, a mapping and logical relationship between individuals and stroke influencing factors is established, so as to predict individual stroke and provide corresponding medical prevention measures.

3. The method for constructing a medical service system for stroke prediction and analysis according to claim 1, characterized in that: The step S2 comprises: Based on the individual body index data in the stroke database and the real-time detection data of wearable hardware detection devices, a mathematical model of intelligent stroke prediction and analysis is constructed to establish a dynamic and individually different stroke prediction and analysis evaluation index system suitable for different users, make a qualitative evaluation of stroke prediction and analysis, and clarify the classification characteristics.

4. The method for constructing a medical service system for stroke prediction and analysis according to claim 3, characterized in that: When establishing a dynamic stroke prediction analysis and evaluation index system suitable for different users and with individual differences, a stroke intelligent prediction mathematical model based on Markov Chain is established based on the four main factors for predicting and judging the development of stroke; Among them, the four main factors include blood lipids and liver function biochemical indicators obtained from blood and secretion body fluid examinations; heart rate, body temperature, blood pressure, carotid artery pulsation, and sleep physiological indicators; height, weight, facial expression, skin appearance, hair appearance, appetite, and head sensation body surface indicators; physical exercise level, memory, perception ability, drinking, smoking, and medical history physical function indicators.

5. The method for constructing a medical service system for stroke prediction and analysis according to claim 3, characterized in that: The establishment of a mathematical model for intelligent stroke prediction based on Markov Chain includes: First, construct a vector set of the probability of occurrence of indicators required to predict stroke: Will Defined as 4 indicator vector sets respectively, construct the Markov chain transfer chain probability matrix of stroke judgment factors : ； in, m=i,j,h,kn=i,j,h,k; According to the properties of Markov chain probability distribution, the transfer matrix is ​​a positive definite matrix, and the sum of the probabilities of each row is equal to 1; ； Secondly, determine the probability of individual stroke prediction and judgment index vector : It is necessary to construct a 4th-order bias weight matrix, combine the Markov Chain with the neural network intelligent learning structure, and use parameters and activation functions to fit the true functional relationship between stroke characteristics and prediction and judgment as closely as possible; the constructed bias weight coefficient is ,in m≠n,m,n=I,j,h,k ; Then, the probability of multi-factor judgment index of individual difference stroke was constructed; According to gender, the subjective indicators of age, BMI, heart rate, blood pressure, carotid pulse, sleep, physical exercise level, head feeling, memory, perception, drinking, smoking and the objectively detectable current moment indicators are defined as , is the previous value of the indicator at the current moment, is the mean value of the indicator at the current moment; For statistics and and Statistics of different relationships: ； ； The current moment indicator Contribution rate of indicators to stroke incidence; ； Finally, the stroke risk probability and response measures are determined based on the risk matrix: according to The probability distribution divides the stroke risk level into five intervals: extreme risk above 90%, high risk 70%-90%, risk 40%-70%, lower risk 10%-40%, and low risk below 10%; For different indicators The percentage of the number to the total number of indicators is defined as the individual contribution ratio of stroke: ； Various subjective and objective indicators such as age, BMI, heart rate, blood pressure, carotid pulse, sleep, physical exercise level, head feeling, memory, perception, drinking, and smoking are set as spatial percentage vectors; Then by physical indicators , Individual contribution ratio of stroke % and the probability of multi-factor judgment index of stroke In the set of spatial vectors formed, different coping measures taken by different individuals to stroke are determined.

6. The method for constructing a medical service system for stroke prediction and analysis according to claim 1, characterized in that: The step S4 comprises: Based on the individual differences in health care needs of users, a medical resource guarantee mechanism is established to guarantee the medical resources required for stroke prevention for ordinary users, an operating mechanism is established to absorb different medical service resources and expand the scope of medical services, and while ensuring that system users can receive medical services in a timely manner and meet their health needs, a reasonable allocation and scheduling of medical service resources is established.

7. The method for constructing a medical service system for stroke prediction and analysis according to claim 1, characterized in that: The step S5 comprises: The intelligent stroke prevention service platform is located at the core position connecting users with different stroke medical service resources. It has the medical service functions of providing individual differences in stroke prediction and prevention, and intelligent configuration of medical resources for ordinary users. On this platform, a stroke prediction mathematical model is built based on Markov Chain, combined with the data in the stroke database, and mapped and matched with stroke medical service resources through intelligent data analysis. According to the physical health data provided by the user in real time through hardware detection equipment, it can predict and analyze the results of stroke and meet the actual use needs of scheduling and matching between users and stroke medical service resources in real time.

8. A medical service device established by the method for constructing a medical service system for stroke prediction and analysis as claimed in claim 1, characterized in that: include: Wearable hardware testing equipment; Intelligent terminal module, bidirectionally connected to wearable hardware detection equipment; An intelligent AI module is bidirectionally connected to the intelligent terminal module. The intelligent AI module includes an intelligent AI data analysis module and an intelligent AI analysis model for health data. The intelligent AI analysis model for health data is used to receive data information of different medical resources. The intelligent AI data analysis module is used to receive the user's individual health data integrated by the intelligent terminal module, and form a mapping and logical deduction with the intelligent AI analysis model for health data, and finally feed back the user's health data analysis results and the optimal medical service plan; The medical service module is bidirectionally connected to the intelligent AI module.

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