Insurance disease standardization digital platform based on artificial intelligence

Abstract

The invention discloses an insurance disease standardization digital platform based on artificial intelligence, and the platform comprises an insurance disease standardization digital platform. The insurance disease standardization digital platform comprises a data collection and integration module, a disease standardization module, an intelligent module, an intelligent identification and diagnosis module, a data mining and analysis module, and a risk assessment and prediction model construction and data security and maintenance module. The digital platform for insurance disease standardization comprises a data collection and integration module, a disease standardization module, an intelligent module, an intelligent identification and diagnosis module, a data mining and analysis module, and a risk assessment and prediction model construction and data security and maintenance module. Disease definitions can be effectively unified, diagnosis standards are defined, and disputes in the claim settlement process are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of insurance digital platforms, and more specifically to an insurance disease standardization digital platform based on artificial intelligence. Background Art

[0002] Insurance disease standardization is the process of ensuring uniform and clear definitions and classifications of various diseases in the insurance industry. It helps insurance companies, medical institutions, regulatory authorities and consumers to achieve efficient communication and seamless connection in disease identification, risk assessment and claims processing. Insurance disease standardization first requires clear definitions of various diseases, including their causes, symptoms, diagnostic criteria and treatment methods. This helps to eliminate ambiguity in the understanding of diseases and ensure that all parties are consistent in the identification and understanding of diseases.

[0003] At present, the digital platform of the insurance industry is not standardized, and the disease definition and diagnostic criteria are not unified, which leads to constant disputes in the claims process. Therefore, a new technical solution is needed to solve this problem. Summary of the invention

[0004] The purpose of the present invention is to provide a digital platform for insurance disease standardization based on artificial intelligence, which solves the problems that the current digital platform in the insurance industry has a low degree of standardization, inconsistent disease definitions, and unclear diagnostic standards, which lead to constant disputes in the claims process.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an artificial intelligence-based digital platform for insurance disease standardization, comprising: an insurance disease standardization digital platform, the insurance disease standardization digital platform comprising a data collection and integration module, a disease standardization module, an intelligent module, an intelligent identification and diagnosis module, a data mining and analysis module, a risk assessment and prediction model construction and a data security and maintenance module, the disease standard module comprising an insurance disease classification module and a standard process module;

[0006] The insurance disease classification module includes a disease classification and coding system. The disease classification systematically classifies diseases in the insurance industry according to the nature, cause, pathology and other characteristics of the disease for easy management and analysis. The coding system assigns a unique code to each disease classification to ensure accurate identification and rapid retrieval of disease information, while facilitating data analysis and mining;

[0007] The standard process module includes process sorting and process optimization. The process sorting comprehensively sorts out the entire process of insurance disease standardization, clarifies the responsibilities, tasks and time nodes of each link, and the process optimization simplifies and optimizes the process on the basis of sorting out, removes redundant links, and improves the efficiency of process execution. The standardized formulation of diseases can effectively unify the definition of diseases, clarify the diagnostic standards, and reduce disputes in the claims process;

[0008] The intelligent module includes artificial intelligence technology, distributed database and cloud computing platform. The artificial intelligence technology is based on platform requirements and selects mature, stable and high-performance artificial intelligence technology, such as deep learning and natural language processing, to ensure the reliable implementation of platform functions. Artificial intelligence technology can automatically process and analyze large amounts of data to improve processing efficiency; at the same time, it continuously optimizes models through machine learning to improve prediction accuracy. The distributed database meets the storage and query requirements of massive data and ensures the stability and performance of the system in high-concurrency scenarios. The cloud computing platform realizes dynamic allocation and elastic expansion of computing resources, reduces operating costs, and ensures the reliability and security of the system.

[0009] As a preferred implementation of the present invention, the data collection and integration module includes a data collection module and a data integration and standardization module.

[0010] As a preferred implementation of the present invention, the data collection module includes a medical institution interface, a health device interface and health APP data synchronization.

[0011] As a preferred implementation mode of the present invention, the data integration and standardization module includes data cleaning, data standardization and database construction.

[0012] As a preferred embodiment of the present invention, the intelligent identification and diagnosis module includes symptom recognition, disease auxiliary diagnosis and intelligent analysis of medical record data.

[0013] As a preferred embodiment of the present invention, the data mining and analysis module includes patient data analysis, diagnosis and treatment effect analysis and medical resource optimization.

[0014] As a preferred embodiment of the present invention, the risk assessment and prediction model construction includes disease risk assessment, diagnosis and treatment result prediction and health status prediction.

[0015] As a preferred implementation mode of the present invention, the data security and maintenance module includes a data encryption module, an access control module, a security audit module and a security maintenance module.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The digital platform for insurance disease standardization of the present invention includes a data collection and integration module, a disease standardization module, an intelligent module, an intelligent identification and diagnosis module, a data mining and analysis module, a risk assessment and prediction model construction and a data security and maintenance module, wherein the disease standard module includes an insurance disease classification module and a standard process module, the insurance disease classification module includes a disease classification and coding system, the disease classification systematically classifies diseases in the insurance industry according to the nature, cause, pathology and other characteristics of the disease, so as to facilitate management and analysis, the coding system assigns a unique code to each disease classification, ensures accurate identification and rapid retrieval of disease information, and facilitates data analysis and mining, the standard process module includes process combing and process optimization, wherein the process combing comprehensively combs the entire process of insurance disease standardization, clarifies the responsibilities, tasks and time nodes of each link, and the process optimization is in the combing On the basis of management, the process is simplified and optimized, redundant links are removed, and the efficiency of process execution is improved. The standardized formulation of diseases can effectively unify the definition of diseases, clarify the diagnostic standards, and reduce disputes in the claims process. The intelligent module includes artificial intelligence technology, distributed database and cloud computing platform. Artificial intelligence technology is based on platform requirements and selects mature, stable and high-performance artificial intelligence technologies, such as deep learning and natural language processing, to ensure the reliable implementation of platform functions. Artificial intelligence technology can automatically process and analyze large amounts of data and improve processing efficiency; at the same time, through machine learning, the model is continuously optimized to improve prediction accuracy. The distributed database meets the storage and query needs of massive data and ensures the stability and performance of the system in high-concurrency scenarios. The cloud computing platform realizes dynamic allocation and elastic expansion of computing resources, reduces operating costs, and ensures the reliability and security of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic diagram of a digital platform for insurance disease standardization according to the present invention;

[0019] Figure 2 This is a schematic diagram of the data collection and integration module of the present invention;

[0020] Figure 3 This is a schematic diagram of the disease standardization module of the present invention;

[0021] Figure 4 This is a schematic diagram of the intelligent module of the present invention;

[0022] Figure 5 This is a schematic diagram of the intelligent identification and diagnosis module of the present invention;

[0023] Figure 6 This is a schematic diagram of the data mining and analysis module of the present invention;

[0024] Figure 7A schematic diagram of the risk assessment and prediction model of the present invention;

[0025] Figure 8 This is a schematic diagram of the data security and maintenance module of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] See also Figure 1-8 , the present invention provides a technical solution: a digital platform for insurance disease standardization based on artificial intelligence, including: a digital platform for insurance disease standardization, the digital platform for insurance disease standardization includes a data collection and integration module, a disease standardization module, an intelligent module, an intelligent identification and diagnosis module, a data mining and analysis module, a risk assessment and prediction model construction and a data security and maintenance module, and the disease standard module includes an insurance disease classification module and a standard process module;

[0028] The insurance disease classification module includes a disease classification and coding system. The disease classification systematically classifies diseases in the insurance industry according to the nature, cause, pathology and other characteristics of the disease for easy management and analysis. The coding system assigns a unique code to each disease classification to ensure accurate identification and rapid retrieval of disease information, while facilitating data analysis and mining;

[0029] The standard process module includes process sorting and process optimization. The process sorting comprehensively sorts out the entire process of insurance disease standardization, clarifies the responsibilities, tasks and time nodes of each link, and the process optimization simplifies and optimizes the process on the basis of sorting out, removes redundant links, and improves the efficiency of process execution. The standardized formulation of diseases can effectively unify the definition of diseases, clarify the diagnostic standards, and reduce disputes in the claims process;

[0030] The intelligent module includes artificial intelligence technology, distributed database and cloud computing platform. The artificial intelligence technology is based on platform requirements and selects mature, stable and high-performance artificial intelligence technology, such as deep learning and natural language processing, to ensure the reliable implementation of platform functions. Artificial intelligence technology can automatically process and analyze large amounts of data to improve processing efficiency; at the same time, it continuously optimizes models through machine learning to improve prediction accuracy. The distributed database meets the storage and query requirements of massive data and ensures the stability and performance of the system in high-concurrency scenarios. The cloud computing platform realizes dynamic allocation and elastic expansion of computing resources, reduces operating costs, and ensures the reliability and security of the system.

[0031] Further improvements, such as Figure 2 As shown: the data collection and integration module includes a data collection module and a data integration and standardization module. The data collection module is responsible for collecting disease-related data from various sources, and the data integration and standardization module cleans, integrates and standardizes the collected data to ensure the quality and consistency of the data.

[0032] Further improvements, such as Figure 2 As shown: the data collection module includes a medical institution interface, a health device interface and a health APP data synchronization. The medical institution interface connects to major medical institutions to obtain patients' diagnosis reports, treatment records and other medical data in real time. The health device interface is connected to wearable devices, health monitoring instruments, etc. to collect users' daily health data. The health APP data synchronization is used to synchronize the personal information and health data entered by users on various health apps.

[0033] Further improvements, such as Figure 2 As shown: the data integration and standardization module includes data cleaning, data standardization and database construction. The data cleaning removes duplicate, erroneous or invalid data. The data standardization converts data from different sources and formats into a standard format recognizable by the platform. The data warehouse construction establishes an efficient data storage and query mechanism to support subsequent data analysis.

[0034] Further improvements, such as Figure 5 As shown: the intelligent identification and diagnosis module includes symptom recognition, disease-assisted diagnosis and intelligent analysis of medical record data. The symptom recognition uses natural language processing technology to intelligently identify patient symptom descriptions to provide a preliminary basis for diagnosis. The disease-assisted diagnosis combines deep learning and medical knowledge graphs to assist doctors in disease diagnosis and improve diagnostic accuracy. The intelligent analysis of medical record data performs intelligent analysis on massive case data, explores disease patterns and potential associations, and provides strong support for medical research.

[0035] Further improvements, such as Figure 6 As shown: the data mining and analysis module includes patient data analysis, diagnosis and treatment effect analysis and medical resource optimization. The patient data analysis analyzes the patient group characteristics and disease spectrum by mining the patient's basic information, medical history, treatment status and other data to provide data support for precision medicine. The diagnosis and treatment effect analysis uses data mining technology to monitor and analyze key indicators in the diagnosis and treatment process, evaluate the effects of different treatment plans, and provide a basis for optimizing treatment strategies. The medical resource optimization is based on the data analysis results to rationally allocate medical resources, such as doctors, drugs, and equipment, to improve the utilization efficiency of medical resources.

[0036] Further improvements, such as Figure 7 As shown: the risk assessment and prediction model construction includes disease risk assessment, treatment result prediction and health status prediction. The disease risk assessment combines patient data and medical knowledge to construct a disease risk assessment model to predict the patient's risk of developing a certain disease and provide a basis for early intervention. The treatment result prediction uses historical data and machine learning algorithms to construct a treatment result prediction model to predict the patient's recovery after treatment and provide a reference for formulating personalized treatment plans. The health status prediction is based on the patient's health data, living habits and other information to predict the patient's future health status trend and provide patients with personalized health management suggestions.

[0037] Further improvements, such as Figure 8 As shown: the data security and maintenance module includes a data encryption module, an access control module, a security audit module and a security maintenance module. The data encryption module encrypts sensitive data to ensure the security of data during transmission and storage, and prevents data leakage and illegal access. The access control module implements strict access control policies, sets different data access rights for different users, and ensures the legal use and operation of data. The security audit module regularly performs security audits on the system to check for potential security vulnerabilities and hidden dangers, and takes preventive measures in a timely manner to ensure the safe and stable operation of the system. The security maintenance module establishes a complete operation and maintenance system to achieve real-time monitoring, fault warning and rapid recovery of the system.

[0038] Working principle: The digital platform for insurance disease standardization includes data collection and integration module, disease standardization module, intelligent module, intelligent identification and diagnosis module, data mining and analysis module, risk assessment and prediction model construction and data security and maintenance module. The disease standard module includes insurance disease classification module and standard process module. The insurance disease classification module includes disease classification and coding system. Disease classification systematically classifies diseases in the insurance industry according to the nature, cause, pathology and other characteristics of the disease for easy management and analysis. The coding system assigns a unique code to each disease classification to ensure accurate identification and rapid retrieval of disease information, and facilitates data analysis and mining. The standard process module includes process combing and process optimization. The process combing comprehensively combs the entire process of insurance disease standardization, clarifies the responsibilities, tasks and time nodes of each link, and optimizes the process. On the basis of sorting, the process is simplified and optimized, redundant links are removed, and the efficiency of process execution is improved. The standardized formulation of diseases can effectively unify the definition of diseases, clarify the diagnostic standards, and reduce disputes in the claims process. The intelligent module includes artificial intelligence technology, distributed database and cloud computing platform. Artificial intelligence technology is based on platform requirements and selects mature, stable and high-performance artificial intelligence technologies, such as deep learning and natural language processing, to ensure the reliable implementation of platform functions. Artificial intelligence technology can automatically process and analyze large amounts of data and improve processing efficiency; at the same time, through machine learning, the model is continuously optimized to improve prediction accuracy. The distributed database meets the storage and query needs of massive data and ensures the stability and performance of the system in high-concurrency scenarios. The cloud computing platform realizes dynamic allocation and elastic expansion of computing resources, reduces operating costs, and ensures the reliability and security of the system.

[0039] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0040] Finally, a few points should be explained: First, in the description of this application, it should be noted that, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, and can be mechanical or electrical connections, or internal connectivity between two components, or direct connections. "Up", "down", "left", "right", etc. are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may change.

[0041] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A digital platform for insurance disease standardization based on artificial intelligence, characterized by: include: A digital platform for insurance disease standardization, wherein the digital platform includes a data collection and integration module, a disease standardization module, an intelligent module, an intelligent identification and diagnosis module, a data mining and analysis module, a risk assessment and prediction model construction module, and a data security and maintenance module. The disease standard module includes an insurance disease classification module and a standard process module. The insurance disease classification module includes a disease classification and coding system. The disease classification systematically classifies diseases in the insurance industry according to the nature, cause, pathology and other characteristics of the disease for easy management and analysis. The coding system assigns a unique code to each disease classification to ensure accurate identification and rapid retrieval of disease information, while facilitating data analysis and mining; The standard process module includes process sorting and process optimization. The process sorting comprehensively sorts out the entire process of insurance disease standardization, clarifies the responsibilities, tasks and time nodes of each link, and the process optimization simplifies and optimizes the process on the basis of sorting out, removes redundant links, and improves the efficiency of process execution. The standardized formulation of diseases can effectively unify the definition of diseases, clarify the diagnostic standards, and reduce disputes in the claims process; The intelligent module includes artificial intelligence technology, distributed database and cloud computing platform. The artificial intelligence technology is based on platform requirements and selects mature, stable and high-performance artificial intelligence technology, such as deep learning and natural language processing, to ensure the reliable implementation of platform functions. Artificial intelligence technology can automatically process and analyze large amounts of data to improve processing efficiency; at the same time, it continuously optimizes models through machine learning to improve prediction accuracy. The distributed database meets the storage and query requirements of massive data and ensures the stability and performance of the system in high-concurrency scenarios. The cloud computing platform realizes dynamic allocation and elastic expansion of computing resources, reduces operating costs, and ensures the reliability and security of the system.

2. According to claim 1, a digital platform for insurance disease standardization based on artificial intelligence is characterized by: The data collection and integration module includes a data collection module and a data integration and standardization module.

3. The digital platform for insurance disease standardization based on artificial intelligence according to claim 2 is characterized by: The data collection module includes a medical institution interface, a health device interface and health APP data synchronization.

4. The digital platform for insurance disease standardization based on artificial intelligence according to claim 1 is characterized by: The data integration and standardization module includes data cleaning, data standardization and database construction.

5. The digital platform for insurance disease standardization based on artificial intelligence according to claim 1 is characterized by: The intelligent identification and diagnosis module includes symptom recognition, disease-assisted diagnosis and intelligent analysis of medical record data.

6. The digital platform for insurance disease standardization based on artificial intelligence according to claim 1 is characterized by: The data mining and analysis module includes patient data analysis, diagnosis and treatment effect analysis and medical resource optimization.

7. The digital platform for insurance disease standardization based on artificial intelligence according to claim 1 is characterized by: The risk assessment and prediction model construction includes disease risk assessment, diagnosis and treatment result prediction and health status prediction.

8. The digital platform for insurance disease standardization based on artificial intelligence according to claim 1 is characterized by: The data security and maintenance module includes a data encryption module, an access control module, a security audit module and a security maintenance module.

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