Large health service management system based on AI technology

Abstract

The invention discloses a big health service management system based on an AI technology. The big health service management system comprises a data center module, a health management module, a medical service module and a health care service module. According to the invention, based on the AI technology, in combination with various modal data such as texts, images, time sequences and the like, a multi-modal fused large health service management model is constructed, more accurate health prediction and diagnosis can be realized, and through the application of the system, the health data management efficiency can be improved, the data security can be guaranteed, and multi-party cooperative service can be realized. Through deep integration of an AI technology and a vertical domain model, the platform is promoted to be upgraded from function integration to intelligent driving and multi-mode cooperation, comprehensive optimization of health management, medical services and medical and nursing services is realized, and more efficient, accurate and humanized health services are provided for residents.

Description

Technical Field

[0001] The present invention relates to the field of medical health information technology, and in particular to a big health service management system based on AI technology. Background Art

[0002] The existing big health service management platforms generally have the following problems:

[0003] 1. Data silo problem: Health records are scattered across different institutions, making cross-platform sharing difficult;

[0004] 2. It is difficult to form a dynamic health portrait in a timely manner based on health data, which is not conducive to effective health management;

[0005] 3. Clinical disease intervention methods lack massive data comparison and selection;

[0006] 4. The health care module has a single function, which makes it difficult to meet diverse needs and cannot be customized;

[0007] 5. Insufficient security: Traditional databases are susceptible to tampering, and the risk of user privacy leakage is high;

[0008] 6. Complex operation: The user appointment and reimbursement process is cumbersome, and the hospital data entry efficiency is low;

[0009] 7. Regulatory lag: Government regulatory agencies require different data, and statistics rely on manual classification and aggregation, resulting in insufficient timeliness and accuracy of data.

[0010] 8. There is a lack of processing and integration of collected multimodal data, resulting in data barriers. Summary of the Invention

[0011] In response to the above problems, the present invention provides a big health service management system based on AI technology. Based on AI technology, it combines multiple modal data such as text (medical records, health records), images (medical imaging), time series (health monitoring data), etc. to construct a multimodal fusion big health service management model, which can achieve more accurate intelligent health management covering the entire process of prevention, diagnosis, treatment, rehabilitation, and elderly care.

[0012] The technical solutions of the present invention are as follows:

[0013] An AI-based health service management system, built on integrated blockchain, intelligent middleware, and AI technologies, enables secure sharing of health data, proactive response to user needs, efficient hospital management, and cross-departmental collaborative services, upgrading from functional integration to intelligent-driven and multi-modal collaboration. This system includes:

[0014] The data center module, based on AI-based data integration capabilities, deeply integrates and intelligently analyzes existing health management, medical, and wellness data with external data including medical insurance systems, public health data, third-party health monitoring equipment data, insurance data, bank data, and customer demand data sources;

[0015] The health management module interacts and shares data with the data center module to build personalized health management models and disease prediction models. The health management model analyzes user health data in real time to form a dynamic health profile of the customer, providing personalized health advice plans. The disease prediction model promptly pushes health risk warning information, and combines the knowledge graph of AI technology to provide comprehensive disease information and AI-assisted diagnosis information.

[0016] The medical service module interacts and shares data with the data center module, tracing back patients' multiple medical visits and building an intelligent consultation model. The model automatically recommends appropriate departments and doctors based on symptom descriptions, and combines AI-assisted diagnostic tools for remote diagnosis and treatment. It also conducts comprehensive analysis of symptoms, signs, and examination results to provide diagnostic recommendations that integrate traditional Chinese and Western medicine.

[0017] The health care service module interacts and shares data with the data center module to build a health care service model. Through the health care service model, it integrates data information from multiple dimensions including daily life, security, health care and rehabilitation, medical care, entertainment and leisure, elderly affairs and learning sharing, builds a comprehensive life service and management system, and provides personalized health care service plans based on the user's health status and preferences.

[0018] In a further technical solution, the system further includes:

[0019] The blockchain health record module uses consortium chain technology to build distributed electronic health records (EHRs), ensuring that data cannot be tampered with and can be shared reliably across institutions;

[0020] The IoT platform module is used to achieve data access and real-time monitoring between the health management module, medical service module, and wellness service module and smart devices, and to perform intelligent management of smart devices based on AI technology;

[0021] The smart device middleware module is used to uniformly access data from multi-brand smart wearable devices and various data sources, and achieve real-time synchronization and analysis through standardized interfaces.

[0022] In a further technical solution, the system further includes:

[0023] The data security and privacy protection module, based on data security technology, encrypts and desensitizes user data, implements a dual security mechanism of storage encryption and transmission signature verification, ensures the security of data during transmission and storage, and combines privacy computing technology to achieve data availability and invisibility, protecting user privacy while supporting data sharing and analysis.

[0024] In a further technical solution, the system further includes:

[0025] The system operation and optimization module, based on AI monitoring tools, monitors system performance in real time, automatically optimizes resource allocation, and establishes a dynamic supervision dashboard to ensure the efficient operation of the system. It also utilizes the continuous learning ability of AI technology to continuously optimize model performance based on user feedback and new data, thereby improving the intelligence level of the system.

[0026] In a further technical solution, the system further includes:

[0027] The intelligent customer service and user support module uses the natural language processing capabilities of AI technology to build an intelligent customer service system to answer user questions in real time and improve user experience.

[0028] In a further technical solution, the system further includes:

[0029] The policy interpretation and push module, based on the knowledge graph of AI technology, provides users with the latest health policy interpretation and push, helping users better enjoy policy benefits.

[0030] In a further technical solution, the system further includes:

[0031] The regulatory data support module is used to provide data support for regulatory authorities. It analyzes system operation data through large models to ensure the compliance and security of the system, and ensure that the big health service management system is upgraded to an intelligent and personalized smart medical and health care platform to better serve the health management of the whole people and promote the development of the big health industry.

[0032] In a further technical solution, the medical service module further includes:

[0033] The treatment plan optimization submodule is interconnected with various information systems within the hospital, and can retrieve patients' previous medical information and health records in real time to provide doctors with decision-making support for traditional Chinese medicine syndrome differentiation and treatment and Western medicine evidence-based medicine, optimize treatment plans, realize automatic generation and intelligent quality control of medical records, reduce doctors' clerical workload, improve medical record quality and medical safety, and conduct real-time review of medical records to promptly detect omissions and errors.

[0034] In a further technical solution, the health care service module further includes:

[0035] The intelligent aging-friendly renovation suggestion sub-module is used to use large models to analyze the user's living environment, intelligently analyze the needs of elderly people at different levels, accurately match service content, and provide intelligent suggestions for aging-friendly renovation.

[0036] The beneficial effects of the present invention are:

[0037] The system of the present invention is a large-scale health service management platform optimization system based on blockchain technology, intelligent device middleware, and AI technology. Through the application of the system of the present invention, the efficiency of health data management can be improved, data security can be guaranteed, and multi-party collaborative services can be realized. By deeply integrating AI technology with vertical domain models, the platform is promoted from "functional integration" to "intelligent drive + multimodal collaboration", achieving comprehensive optimization of health management, medical services, and medical care services, providing residents with more efficient, accurate, and humane health services. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a schematic structural diagram of the system described in Example 1 of the present invention;

[0039] Figure 2 This is a schematic diagram of information data flow in the system described in Example 1 of the present invention;

[0040] Figure 3 This is a schematic diagram of the structure of the IoT platform module described in Example 1 of the present invention;

[0041] Figure 4 This is an external application scenario diagram of the platform described in Example 2 of the present invention;

[0042] Figure 5 This is the internal management logic diagram of the platform described in Example 2 of the present invention;

[0043] Figure 6 This is a system architecture diagram of the platform described in Example 2 of the present invention;

[0044] Figure 7 This is the overall data flow diagram of the platform described in Example 2 of the present invention;

[0045] Figure 8 This is a data flow diagram of the health management module in the platform described in Example 2 of the present invention;

[0046] Figure 9 This is a data flow diagram of the medical service module in the platform described in Example 2 of the present invention;

[0047] Figure 10 This is a system network topology diagram of the platform described in Example 2 of the present invention. DETAILED DESCRIPTION

[0048] The embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0049] Example 1:

[0050] like Figure 1-2 As shown in the figure, a big health service management system based on AI technology is built based on integrated blockchain, intelligent middle platform and AI technology. It realizes the secure sharing of health data, proactive response to user needs, efficient hospital management and cross-departmental collaborative services from functional integration to intelligent drive + multi-modal collaboration, including:

[0051] The data center module, based on AI-based data integration capabilities, deeply integrates and intelligently analyzes existing health management, medical, and wellness data with external data including medical insurance systems, public health data, third-party health monitoring equipment data, insurance data, bank data, and customer demand data sources;

[0052] The health management module interacts and shares data with the data center module to build personalized health management models and disease prediction models. The health management model analyzes user health data in real time to form a dynamic health profile of the customer, providing personalized health advice plans. The disease prediction model promptly pushes health risk warning information, and combines the knowledge graph of AI technology to provide comprehensive disease information and AI-assisted diagnosis information.

[0053] The medical service module interacts and shares data with the data center module, tracing back patients' multiple medical visits and building an intelligent consultation model. The model automatically recommends appropriate departments and doctors based on symptom descriptions, and combines AI-assisted diagnostic tools for remote diagnosis and treatment. It also conducts comprehensive analysis of symptoms, signs, and examination results to provide diagnostic recommendations that integrate traditional Chinese and Western medicine.

[0054] The health care service module interacts and shares data with the data center module to build a health care service model. Through the health care service model, it integrates data information from multiple dimensions including daily life, security, health care and rehabilitation, medical care, entertainment and leisure, elderly affairs and learning sharing, builds a comprehensive life service and management system, and provides personalized health care service plans based on the user's health status and preferences.

[0055] In another embodiment, Figure 3 As shown, the system also includes:

[0056] The blockchain health record module uses consortium chain technology to build distributed electronic health records (EHRs), ensuring that data cannot be tampered with and can be shared reliably across institutions;

[0057] The IoT platform module is used to achieve data access and real-time monitoring between the health management module, medical service module, and wellness service module and smart devices, and to perform intelligent management of smart devices based on AI technology;

[0058] The smart device middleware module is used to uniformly access data from multi-brand smart wearable devices and various data sources, and achieve real-time synchronization and analysis through standardized interfaces.

[0059] In another embodiment, the system further comprises:

[0060] The data security and privacy protection module, based on data security technology, encrypts and desensitizes user data, implements a dual security mechanism of storage encryption and transmission signature verification, ensures the security of data during transmission and storage, and combines privacy computing technology to achieve data availability and invisibility, protecting user privacy while supporting data sharing and analysis.

[0061] In another embodiment, the system further comprises:

[0062] The system operation and optimization module, based on AI monitoring tools, monitors system performance in real time, automatically optimizes resource allocation, and establishes a dynamic supervision dashboard to ensure the efficient operation of the system. It also utilizes the continuous learning ability of AI technology to continuously optimize model performance based on user feedback and new data, thereby improving the intelligence level of the system.

[0063] In another embodiment, the system further comprises:

[0064] The intelligent customer service and user support module uses the natural language processing capabilities of AI technology to build an intelligent customer service system to answer user questions in real time and improve user experience.

[0065] In another embodiment, the system further comprises:

[0066] The policy interpretation and push module, based on the knowledge graph of AI technology, provides users with the latest health policy interpretation and push, helping users better enjoy policy benefits.

[0067] In another embodiment, the system further comprises:

[0068] The regulatory data support module is used to provide data support for regulatory authorities. It analyzes system operation data through large models to ensure the compliance and security of the system, and ensure that the big health service management system is upgraded to an intelligent and personalized smart medical and health care platform to better serve the health management of the whole people and promote the development of the big health industry.

[0069] In another embodiment, the medical service module further includes:

[0070] The treatment plan optimization submodule is interconnected with various information systems within the hospital, and can retrieve patients' previous medical information and health records in real time to provide doctors with decision-making support for traditional Chinese medicine syndrome differentiation and treatment and Western medicine evidence-based medicine, optimize treatment plans, realize automatic generation and intelligent quality control of medical records, reduce doctors' clerical workload, improve medical record quality and medical safety, and conduct real-time review of medical records to promptly detect omissions and errors.

[0071] In another embodiment, the health care service module further includes:

[0072] The intelligent aging-friendly renovation suggestion sub-module is used to use large models to analyze the user's living environment, intelligently analyze the needs of elderly people at different levels, accurately match service content, and provide intelligent suggestions for aging-friendly renovation.

[0073] Age-friendly interactive design: The mobile terminal supports voice navigation, large-font mode, and emergency call linkage functions.

[0074] Example 2:

[0075] In this embodiment, a large health service management platform is built based on the system described in Example 1, wherein: Figure 4 It is the external application scenario diagram of the platform. Figure 5 This is the internal management logic diagram of the platform. Figure 6 This is the system architecture diagram of the platform. Figure 7 This is the overall data flow diagram of the platform. Figure 8 This is the data flow diagram for the health management module. Figure 9 This is the data flow diagram for the medical service module. Figure 10 This is the system network topology diagram of the platform. The following optimizations have also been implemented in the platform:

[0076] Patient information management optimization:

[0077] 1. Data Integration and Standardization: The patient information management module is the foundation of the platform, and its optimization focuses primarily on data integration and standardization. Hospitals currently face the challenge of integrating heterogeneous data from multiple sources, such as electronic medical records (EMRs), laboratory information systems (LISs), and picture archiving and communication systems (PACSs). The optimization solution proposes adopting the HL7 (Health Level Seven) international standard and the FHIR (Fast Healthcare Interoperability Resources) framework to enable data exchange and standardized processing across different systems. This will significantly improve data consistency and availability, laying a solid foundation for subsequent data analysis and intelligent decision-making.

[0078] 2. Intelligent Patient Health Records: Introducing artificial intelligence technology to intelligently categorize and label patient health records, such as automatically generating health risk assessment reports based on medical history, family history, lifestyle habits, and other information. Simultaneously, developing personalized health reminders, such as reminders to take medication on time and schedule follow-up appointments, to notify patients via text messages and app push notifications, enhancing patient engagement and compliance.

[0079] 3. Privacy Protection and Rights Management: During the data integration process, privacy protection measures are strengthened, using technologies such as encrypted storage and access control to ensure patient information security. A hierarchical rights management strategy is implemented, with doctors, nurses, and administrators having different data access permissions based on their roles, ensuring both information security and improving work efficiency.

[0080] Optimization of online diagnosis and treatment service module:

[0081] 1. Video consultation experience upgrade: As a core feature of online diagnosis and treatment, video consultations' smoothness and interactivity directly impact the user experience. Optimization solutions include increasing server bandwidth and adopting high-definition audio and video codec technology to ensure low-latency, high-quality communication between doctors and patients. Additionally, auxiliary features such as virtual backgrounds and beauty filters have been added to enhance user visual comfort.

[0082] 2. Intelligent Assisted Diagnosis System: Incorporating deep learning algorithms, we developed an intelligent assisted diagnosis tool that can rapidly analyze patient symptom descriptions, examination reports, and other data to provide doctors with preliminary diagnostic recommendations, reducing misdiagnosis rates and improving diagnosis and treatment efficiency. The system also continuously learns from doctors' professional judgments, enabling self-iterative optimization.

[0083] 3. Integration of electronic prescriptions and drug delivery: Optimize the electronic prescription process so that once a doctor issues a prescription, the system automatically connects to a partner pharmacy or hospital pharmacy. Patients can choose to pay online, pick up their medication offline, or have it delivered by courier. Blockchain technology ensures the authenticity and immutability of prescription information, safeguarding the security of drug distribution.

[0084] Optimization of health management service module:

[0085] 1. Personalized health management plan: Based on big data analysis, we provide patients with personalized health management plans, including dietary recommendations, exercise guidance, and mental health support. Using machine learning algorithms, we dynamically adjust the plan content based on changes in the patient's health status to achieve precise health management.

[0086] 2. Community Interaction and Psychological Support: Build a patient community, encourage patients to share treatment experiences and recovery stories, and foster a positive recovery atmosphere. At the same time, bring in professional psychological counselors to provide online psychological counseling and intervention services, especially for those with chronic diseases, cancer patients, and other individuals experiencing high levels of psychological stress, providing necessary psychological support.

[0087] 3. Health Monitoring Device Integration: We collaborate with leading health monitoring device manufacturers, such as smart wristbands, blood pressure monitors, and blood glucose meters, to synchronize data to the platform for real-time monitoring of patient health. Combined with AI algorithms, we provide early warnings for abnormal data, promptly notifying patients and medical staff to prevent disease progression.

[0088] Optimization of operations management and data analysis modules:

[0089] 1. Intelligent resource scheduling: Leveraging big data analysis technology to optimize hospital resource allocation, for example, predicting future peak visit times based on historical patient data allows for rational scheduling of medical staff and reduces patient wait times. Furthermore, real-time monitoring and analysis of medical equipment usage provides early warning of maintenance needs, preventing equipment failures from impacting diagnosis and treatment services.

[0090] 2. Operational Performance Evaluation: Establish a comprehensive operational performance evaluation system to quantitatively evaluate each hospital department using key performance indicators (KPIs) such as patient satisfaction, diagnosis and treatment efficiency, and cost control. Utilize visual reporting tools to intuitively display operational data and provide decision support for management.

[0091] 3. Patient Behavior Analysis: We conduct in-depth analysis of patient behavior data on the platform, such as visit frequency, dwell time, and feature preferences, to gain insights into user needs and continuously optimize product design and service processes. We use methods such as A / B testing to verify the effectiveness of new features and ensure that each iteration has a positive impact.

[0092] Example 3:

[0093] This embodiment integrates AI technology with the electronic medical record system.

[0094] Electronic medical records (EMRs) are an essential core system for modern healthcare institutions, recording critical patient data such as diagnosis and treatment information, test results, and medication history. The integration of AI technology into EMRs aims to enable comprehensive sharing of patient information, improve the accuracy of medical decision-making, and optimize medical staff's workflow.

[0095] The specific integration solution is as follows:

[0096] Data interface design: Define the data interaction interface between AI technology and EMR systems to ensure real-time data transmission and unified format. This includes the synchronization of basic patient information, medical records, examination results, and other data.

[0097] Database integration: Consider using a unified database management system or establishing data middleware to achieve data consistency and integrity between the two systems.

[0098] Functional integration: Embed the core functions of the EMR system, such as medical record review and doctor order entry, into AI technology, allowing medical staff to complete daily diagnosis and treatment work without switching systems.

[0099] Through integration, medical staff can directly access and edit patients' electronic medical records on the AI ​​platform, improving work efficiency. At the same time, the platform can use data from the EMR system to provide patients with more personalized health management recommendations.

[0100] Example 4:

[0101] This embodiment integrates AI technology with the regional health information platform.

[0102] The regional health information platform is a crucial link connecting medical institutions at all levels within the region, enabling the sharing of medical resources and the exchange of medical information. The integration of AI technology into the regional health information platform aims to broaden the platform's data sources and enhance regional medical collaboration.

[0103] The specific integration solution is as follows:

[0104] Data Sharing Agreement: Sign a data sharing agreement with the regional health information platform to clarify the scope, methods and security responsibilities of data sharing.

[0105] Interface connection: Develop a data interface to achieve real-time data synchronization between AI technology and regional health information platforms. This includes basic patient information, medical records, public health data, etc.

[0106] Business collaboration: Embed regional medical collaboration functions such as two-way referral and remote consultation into AI technology to improve the utilization efficiency of regional medical resources.

[0107] Through integration, the AI ​​platform can access patient and medical resource information from regional health information platforms in real time, providing more comprehensive data support for medical staff. At the same time, the platform can facilitate regional medical collaboration and improve the overall efficiency of medical services.

[0108] Example 5:

[0109] This embodiment integrates AI technology with a health management APP.

[0110] Health management apps are essential tools for modern health management, providing functions such as health monitoring, health consultation, and health planning. The integration of AI technology with health management apps aims to comprehensively collect and analyze patient health data, providing patients with more personalized health management services.

[0111] The specific integration solution is as follows:

[0112] API interface development: Develop API interfaces to enable data interoperability between AI technology and health management apps. This includes patient health monitoring data, health plan execution status, etc.

[0113] Functional integration: Embed the core functions of the health management app into AI technology, such as health monitoring reminders and health plan formulation, so that patients can complete the entire health management process on the platform.

[0114] Data synchronization and analysis: Synchronize the data in the health management app with the data of AI technology, and use big data analysis technology to provide patients with more accurate health management suggestions.

[0115] After integration, patients can upload their health data to the AI ​​platform through the health management app, which can then use this data to provide patients with more personalized health management services. At the same time, patients can view their health plans and health monitoring results on the platform, improving the convenience and efficiency of health management.

[0116] Example 6:

[0117] This embodiment integrates AI technology with the telemedicine system.

[0118] Telemedicine systems are a vital component of modern healthcare, enabling cross-regional sharing of medical resources and facilitating access to healthcare services. The integration of AI technology with telemedicine systems aims to enhance the platform's telemedicine capabilities and provide patients with more convenient healthcare services.

[0119] The specific integration solution is as follows:

[0120] Video communication interface development: Develop a video communication interface to enable video calls between AI technology and telemedicine systems. This includes remote consultations between patients and doctors, remote education, etc.

[0121] Data synchronization and sharing: Realize data synchronization and sharing between AI technology and telemedicine systems, including patient basic information, medical records, examination results, etc.

[0122] Business process optimization: Optimize the telemedicine service process based on AI technology, such as remote consultation appointments and remote teaching arrangements, to improve the convenience and efficiency of services.

[0123] After integration, patients can use the AI ​​platform to schedule remote consultations, conduct video calls with doctors, and obtain professional medical advice. Medical staff can also use the platform for remote teaching and case discussions, improving the overall effectiveness of medical services.

[0124] Example 7:

[0125] This embodiment integrates AI technology with the insurance claims system.

[0126] The insurance claims system is the core system used by insurance companies to process claims. The integration of AI technology into the insurance claims system aims to seamlessly connect medical and insurance claims data, improving claims processing efficiency.

[0127] The specific integration solution is as follows:

[0128] Data interface development: Develop a data interface to enable data interoperability between AI technology and the insurance claims system. This includes patient basic information, medical expense details, diagnosis certificates, etc.

[0129] Business process integration: Embed insurance claims business processes, such as claims application and claims review, into AI technology, enabling patients to complete the entire claims process on the platform.

[0130] Data security and privacy protection: Strengthen data security and privacy protection measures to ensure the secure transmission and storage of medical data and insurance claims data.

[0131] After integration, patients can submit claims through the AI ​​platform, which automatically sends relevant data to the insurance claims system for processing. This not only improves claims processing efficiency but also reduces patient waiting time.

[0132] Example 8:

[0133] This embodiment integrates AI technology with IoT smart devices.

[0134] IoT smart devices are a key innovation in modern healthcare, enabling real-time monitoring and remote transmission of medical data. The integration of AI technology and IoT smart devices aims to broaden the platform's data sources and enhance the accuracy and real-time nature of health management.

[0135] The specific integration solution is as follows:

[0136] Device access agreement: Sign a device access agreement with the IoT smart device manufacturer to clarify the data access method, format and security responsibilities.

[0137] Data interface development: Develop data interfaces to enable data interoperability between AI technology and IoT smart devices. This includes real-time transmission of patient physiological parameters, device status, and other data.

[0138] Data analysis and application: Use big data analysis technology to analyze and apply data collected by IoT smart devices to provide patients with more accurate health management recommendations.

[0139] Once integrated, IoT smart devices can monitor patients' physiological parameters in real time and upload them to the AI ​​platform. The platform can use this data to provide patients with more personalized health management services, such as health alerts and health plan adjustments. Medical staff can also use the platform to view patients' device status and data changes in real time, improving the timeliness and accuracy of medical services.

[0140] The AI ​​technology described in the above embodiments can specifically select the Deep Seek platform.

[0141] The above-described embodiments merely represent specific implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, and all such variations and improvements fall within the scope of protection of the present invention.

Claims

1. A big health service management system based on AI technology, characterized by: The system is built based on integrated blockchain, intelligent middle platform and AI technology, including: The data center module, based on AI-based data integration capabilities, deeply integrates and intelligently analyzes existing health management, medical, and wellness data with external data including medical insurance systems, public health data, third-party health monitoring equipment data, insurance data, bank data, and customer demand data sources; The health management module interacts and shares data with the data center module to build personalized health management models and disease prediction models. The health management model analyzes user health data in real time to form a dynamic health profile of the customer, providing personalized health advice plans. The disease prediction model promptly pushes health risk warning information, and combines the knowledge graph of AI technology to provide comprehensive disease information and AI-assisted diagnosis information. The medical service module interacts and shares data with the data center module, tracing back patients' multiple medical visits and building an intelligent consultation model. The model automatically recommends appropriate departments and doctors based on symptom descriptions, and combines AI-assisted diagnostic tools for remote diagnosis and treatment. It also conducts comprehensive analysis of symptoms, signs, and examination results to provide diagnostic recommendations that integrate traditional Chinese and Western medicine. The health care service module interacts and shares data with the data center module to build a health care service model. Through the health care service model, it integrates data information from multiple dimensions including daily life, security, health care and rehabilitation, medical care, entertainment and leisure, elderly affairs and learning sharing, builds a comprehensive life service and management system, and provides personalized health care service plans based on the user's health status and preferences.

2. The AI-based health service management system according to claim 1 is characterized in that: The system also includes: The blockchain health record module uses consortium chain technology to build distributed electronic health records, ensuring that data cannot be tampered with and can be shared reliably across institutions; The IoT platform module is used to achieve data access and real-time monitoring between the health management module, medical service module, and wellness service module and smart devices, and to perform intelligent management of smart devices based on AI technology; The smart device middleware module is used to uniformly access data from multi-brand smart wearable devices and various data sources, and achieve real-time synchronization and analysis through standardized interfaces.

3. The AI-based health service management system according to claim 1 is characterized in that: The system also includes: The data security and privacy protection module, based on data security technology, encrypts and desensitizes user data, implements a dual security mechanism of storage encryption and transmission signature verification, ensures the security of data during transmission and storage, and combines privacy computing technology to achieve data availability and invisibility, protecting user privacy while supporting data sharing and analysis.

4. The AI-based health service management system according to claim 1, characterized in that: The system also includes: The system operation and optimization module, based on AI monitoring tools, monitors system performance in real time, automatically optimizes resource allocation, and establishes a dynamic supervision dashboard to ensure the efficient operation of the system. It also utilizes the continuous learning ability of AI technology to continuously optimize model performance based on user feedback and new data, thereby improving the intelligence level of the system.

5. The AI-based health service management system according to claim 1 is characterized in that: The system also includes: The intelligent customer service and user support module uses the natural language processing capabilities of AI technology to build an intelligent customer service system to answer user questions in real time and improve user experience.

6. The AI-based health service management system according to claim 1, characterized in that: The system also includes: The policy interpretation and push module, based on the knowledge graph of AI technology, provides users with the latest health policy interpretation and push, helping users better enjoy policy benefits.

7. The AI-based health service management system according to claim 1, characterized in that: The medical service module also includes: The treatment plan optimization submodule is interconnected with various information systems within the hospital, and can retrieve patients' previous medical information and health records in real time to provide doctors with decision-making support for traditional Chinese medicine syndrome differentiation and treatment and Western medicine evidence-based medicine, optimize treatment plans, realize automatic generation and intelligent quality control of medical records, reduce doctors' clerical workload, improve medical record quality and medical safety, and conduct real-time review of medical records to promptly detect omissions and errors.

8. The AI-based health service management system according to claim 1, characterized in that: The health care service module also includes: The intelligent aging-friendly renovation suggestion sub-module is used to use a large model to analyze the user's living environment and provide intelligent suggestions for aging-friendly renovation.

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