A method and system for intelligent assessment of chronic disease health based on data analysis

Abstract

The application discloses a kind of based on data analysis's chronic disease health intelligent evaluation method and system, it is related to chronic disease health intelligent evaluation technical field, the method of the present application includes user health pre-diagnosis, user health assessment, user chronic disease health management and early warning prompt, the multi-source data obtained by user investigation is further analyzed to obtain the pre-diagnosis state of user corresponding health, and corresponding detection is arranged according to the pre-diagnosis state of user, the state of user corresponding chronic disease is evaluated, to execute targeted health management, while collecting the data of user after management, it is evaluated whether the chronic disease health intelligent evaluation and management of health management system corresponding user are effective, to realize the intelligent management and guarantee of user corresponding health, further reduce the serious risk caused by chronic disease discovery too late, realize the timely discovery of chronic disease, make chronic disease get timely discovery and governance, reduce the adverse situation caused by chronic disease.

Description

Technical Field

[0001] This invention relates to the field of intelligent assessment technology for chronic disease health, specifically to a data analysis-based intelligent assessment method and system for chronic disease health. Background Technology

[0002] With the increasing aging of the population and changes in lifestyle, chronic diseases have become the primary challenge for public health. The manifestation of chronic diseases is often insidious and temporary, making them easily overlooked and potentially leading to serious health risks. Therefore, this paper proposes a data-driven intelligent health assessment method and system for chronic diseases. By acquiring multi-level survey data from users, the system intelligently assesses their corresponding health status and implements targeted health management measures based on this status. This approach aims to reduce the incidence of chronic diseases and mitigate the serious complications associated with them, thus intelligently protecting users' health.

[0003] Existing intelligent assessment methods and systems for chronic disease health have at least the following technical problems: Currently, users typically seek medical attention at offline hospitals only after experiencing frequent abnormal reactions to chronic diseases. However, when these examinations are conducted, the available user data is extremely limited, leading to uncertainty about the direction of the disease and wasted time in the screening process. This can delay and worsen chronic diseases, failing to detect them in a timely manner, unable to recommend appropriate pathological examinations based on the user's chronic disease information, and unable to conduct a deeper understanding and assessment of the user's chronic disease condition to collect targeted treatment methods. Consequently, these methods and systems cannot intelligently and effectively protect the user's health. Summary of the Invention

[0004] To address the aforementioned technical shortcomings, the purpose of this invention is to provide a data-based intelligent assessment method and system for chronic disease health.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides a data analysis-based intelligent assessment method for chronic disease health, including: Step 1, user health pre-diagnosis: By performing a corresponding pre-health survey on users who log in to the disease prevention management system, multi-source data of the user's corresponding survey are extracted, and the user's corresponding health pre-diagnosis status is analyzed.

[0006] Step 2, User Health Assessment: Based on the pre-diagnosis results of the user's corresponding health analysis, the system then analyzes and obtains a set of health needs tests for the user's corresponding chronic diseases. The user then performs the corresponding tests according to the test schedule set within the set, obtains the test indicator data for the user's corresponding test set, assesses the user's status of corresponding chronic diseases, and analyzes the health management methods for the user's status.

[0007] Step 3: User Chronic Disease Health Management: By monitoring chronic disease users under health management in real time, the system collects the corresponding status data of users and evaluates whether the intelligent assessment and management of chronic disease health of users corresponding to the health management system is effective.

[0008] Step 4: Early Warning Prompt: An early warning prompt will be issued when the user's pre-diagnosis health status is chronic disease, the user's chronic disease status is high-risk, or the health management system's intelligent assessment and management of the user's chronic disease health is ineffective.

[0009] In a second aspect, the present invention provides a data analysis-based intelligent health assessment system for chronic diseases, comprising: a user health pre-diagnosis module, used to perform a corresponding pre-health survey on users who have logged into disease prevention and management, thereby extracting multi-source data of the user's corresponding survey and analyzing the user's corresponding health pre-diagnosis status.

[0010] The user health assessment module is used to analyze the pre-diagnosis results of the user's corresponding health analysis, and then to obtain the set of health needs testing for the user's corresponding chronic diseases. The user can then perform the corresponding tests according to the test schedule set in the set, obtain the test indicator data of the user's corresponding test set, assess the user's status of the corresponding chronic diseases, and analyze the health management methods for the user's status.

[0011] The user chronic disease health management module is used to monitor chronic disease users under health management in real time, and then collect the corresponding status data of users to evaluate whether the intelligent assessment and management of chronic disease health of users in the health management system is effective.

[0012] The early warning terminal is used to issue early warnings when a user's pre-diagnosis health status is chronic disease, the user's chronic disease status is high-risk, or the health management system's intelligent assessment and management of the user's chronic disease health is ineffective.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. The present invention provides a method and system for intelligent assessment of chronic disease health based on data analysis. By analyzing multi-source data obtained from user surveys, the pre-diagnosis status of the user's corresponding health is obtained, and corresponding tests are arranged for the user's corresponding pre-diagnosis status to assess the status of the user's corresponding chronic disease, thereby implementing targeted health management. At the same time, the data after the user's corresponding management is collected to assess whether the health management system is effective in assessing and managing the user's chronic disease health. This achieves intelligent management and protection of the user's corresponding health, further reducing the serious risks caused by delayed detection of chronic diseases, and achieving timely detection of chronic diseases. This solves the shortcomings of the current technology. At the same time, based on the acquisition of user's multi-faceted survey data, the effective identification of the user's chronic diseases is achieved, effectively improving the efficiency of chronic disease diagnosis and treatment, comprehensively and efficiently protecting the user's health, enabling timely detection and treatment of chronic diseases, and reducing the adverse status quo caused by chronic diseases.

[0014] 2. By conducting health surveys on users, we can extract multi-source data corresponding to the surveys and analyze the users' corresponding health status to achieve timely detection of chronic diseases, so as to take timely chronic disease management measures and reduce the serious risks caused by the continued spread of chronic diseases.

[0015] 3. By analyzing the data, a set of health needs tests for users' chronic diseases is obtained. Users then undergo corresponding tests based on the established testing schedule within this set. The test indicator data for each user's chronic disease is obtained, and the current status of the user's chronic disease is assessed. The analysis reveals the appropriate health management approach for each user's current status. This enables targeted chronic disease testing for users, timely understanding of the current development of their chronic diseases, and implementation of targeted management measures to effectively manage and intelligently inhibit the progression of chronic diseases, thereby protecting the user's health.

[0016] 4. By monitoring chronic disease users under health management in real time, and collecting corresponding status data of users, the effectiveness of the health management system in assessing the effectiveness of chronic disease health intelligent assessment and management of users is obtained, thereby realizing timely detection of chronic diseases, providing users with an effective chronic disease prevention platform, and efficiently protecting users' physical health. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1This is a schematic diagram of the implementation steps of the method of the present invention.

[0019] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1 As shown, a data analysis-based intelligent assessment method for chronic disease health includes: Step 1, user health pre-diagnosis: By performing a corresponding pre-health survey on users who log in to the disease prevention management system, multi-source data of the user's corresponding survey are extracted, and the user's corresponding health pre-diagnosis status is analyzed.

[0022] It should be noted that by conducting health surveys on users, multi-source data corresponding to the surveys can be extracted and analyzed to obtain the user's pre-diagnosis health status, thereby enabling the timely detection of users' chronic diseases, so as to take timely chronic disease management measures and reduce the serious risks caused by the continued spread of chronic diseases.

[0023] It should be noted that the multi-source data was obtained from the pre-health survey forms filled out by users.

[0024] In a specific embodiment of the present invention, the multi-source data includes basic data, traditional Chinese medicine data, psychological data, and other data.

[0025] In a specific embodiment of the present invention, the analysis obtains the user's corresponding health pre-diagnosis status. The specific analysis process is as follows: The multi-source data of the user's survey is compared with the reference multi-source data sets corresponding to each chronic disease stored in the database. If the multi-source data of the user's survey does not overlap with any of the reference multi-source data sets corresponding to each chronic disease stored in the database, it is determined that the user does not have a chronic disease and the user's body is in a healthy state. If the multi-source data of the user's survey overlaps with the reference multi-source data set corresponding to a certain chronic disease stored in the database, it is determined that the user has a chronic disease and the user needs to undergo corresponding in-depth diagnosis and treatment. In this way, the user's corresponding health pre-diagnosis status is obtained through analysis.

[0026] It should be noted that professional physicians set up reference multi-source datasets for each chronic disease based on their knowledge and experience. These datasets serve as comparative references for more intuitively assessing whether a user currently has a chronic disease, thereby enabling timely understanding of the user's health status and providing effective and intelligent health protection.

[0027] Step 2, User Health Assessment: Based on the pre-diagnosis results of the user's corresponding health analysis, the system then analyzes and obtains a set of health needs tests for the user's corresponding chronic diseases. The user then performs the corresponding tests according to the test schedule set within the set, obtains the test indicator data for the user's corresponding test set, assesses the user's status of corresponding chronic diseases, and analyzes the health management methods for the user's status.

[0028] It should be noted that by analyzing and obtaining a set of health needs tests for users' chronic diseases, and having users perform corresponding examinations based on the test schedule set within the set, the system obtains the test indicator data for each user's corresponding chronic disease, assesses the user's current chronic disease status, and analyzes the health management methods for that status. This enables targeted chronic disease testing for users, timely understanding of the current development status of their chronic diseases, and implementation of targeted management measures to effectively manage and intelligently inhibit the progression of chronic diseases, thereby protecting the user's health.

[0029] In a specific embodiment of the present invention, the analysis obtains a set of health needs detection for users corresponding to chronic diseases. The specific analysis process is as follows: Based on the various data contained in the multi-source survey data corresponding to users, the question and answer features corresponding to each data are extracted to form various disease keywords for users corresponding to chronic diseases. The various disease keywords for users corresponding to chronic diseases are compared with the standard disease type keywords corresponding to various examination sets stored in the database. If a certain disease keyword for users corresponding to chronic diseases is consistent with the standard disease type keyword corresponding to a certain examination set stored in the database, then that examination is taken as the need examination item for users corresponding to chronic diseases. In this way, the comparison of various disease keywords is performed to obtain various need examination items for users corresponding to various disease keywords. Based on the comprehensive composition of various need examination items, a set of health needs detection is obtained.

[0030] Simultaneously, based on the disease keywords corresponding to the user's chronic disease, the system compares them with the chronic disease keywords corresponding to the various complication sets stored in the database to obtain the predictive concurrency set for the user's chronic disease. Then, it extracts the disease keywords corresponding to the complications within the concurrency set and compares them with the standard disease type keywords corresponding to the various examination sets stored in the database to obtain the various derivative examination items under the complications. Finally, it integrates the various required examination items under the user's disease keywords to form a health needs detection set.

[0031] Based on a single set of health needs assessments and a set of derivative assessments that add complications to the single assessments, the user's corresponding set of health needs assessments for chronic diseases is analyzed, allowing the user to make any selection.

[0032] It should be noted that professional physicians set the reference multi-source datasets for each chronic disease and the chronic disease keywords for each set of complications; the reference multi-source datasets for each chronic disease are used to determine the reference values ​​for the examination items that users need to perform based on their chronic disease conditions; the reference multi-source datasets for each chronic disease are used to determine whether users need to add derivative testing items for their corresponding chronic diseases.

[0033] In a specific embodiment of the present invention, the inspection indicator data includes conventional indicator values, special indicator values, and other indicator values.

[0034] It should be noted that conventional indicator values ​​include cell count and platelet count, etc.; specific indicator values ​​include organ fluctuation values ​​and organ hormone values, such as organ fluctuation values ​​such as ambulatory blood pressure or vital capacity; organ fluctuation values ​​such as organ hormone values ​​such as sex hormones or insulin, etc.; other indicator values ​​include body fluid values ​​and pathological lesion values, such as body fluid values ​​such as urine glucose or cerebrospinal fluid, etc. The examples given are for illustrative purposes only and are not the only limitations.

[0035] In a specific embodiment of the present invention, the evaluation process for assessing the status of a user's corresponding chronic disease is as follows: the values ​​of the routine indicators, the special indicators, and other indicators under the user's corresponding detection set are denoted as μ, θ, and λ, respectively. If (μ < μ′) ∨ (θ < θ′) ∨ (λ < λ′), then the user's corresponding chronic disease is determined to be in a low-risk state, with a risk of chronic disease complications or malignancy. μ′ is a set reference routine indicator value, θ′ is a set reference special indicator value, λ′ is a set reference other indicator value, and ∨ represents OR.

[0036] If (μ=μ′)∧(θ=θ′)∧(λ=λ′), then the user's corresponding chronic disease is determined to be in a normal state, with no risk of chronic disease mutation or malignancy. ∧ represents the sum.

[0037] If (μ>μ′)∨(θ>θ′)∨(λ>λ′), then the user's chronic disease is determined to be in a high-risk state, with the risk of chronic disease complications or malignant risks.

[0038] It should be noted that when a user's chronic disease is in a normal state, and there is no risk of disease mutation or malignancy, then the user should simply follow the doctor's instructions and scheduled follow-up appointments. For example, precautions include avoiding spicy and high-sugar foods. A professional physician will set reference values ​​for routine indicators, specific indicators, and other indicators. These reference values ​​are used to assess the user's chronic disease status, and the examples given are for illustrative purposes only and are not the only possible interpretations.

[0039] In a specific embodiment of the present invention, the analysis obtains the health management method corresponding to the user's current state. The specific analysis process is as follows: When the user's chronic disease is at low risk: Based on the health test set corresponding to the low-risk chronic disease user, the corresponding chronic disease type is obtained. The chronic disease type corresponding to the low-risk chronic disease user is compared with the various chronic disease type sets stored in the database. If the chronic disease type corresponding to the low-risk chronic disease user is consistent with a certain chronic disease type set stored in the database, then the standard treatment method corresponding to that chronic disease type set is used as the health management method for the low-risk chronic disease user.

[0040] When a user's chronic disease is at high risk, the chronic disease type of the high-risk chronic disease user is compared with the disease specialty set of each TCM doctor. The TCM doctors who can treat the chronic disease type of the high-risk chronic disease user are selected, and a secondary analysis of the indicator data of the health test set of each TCM doctor corresponding to the high-risk chronic disease user is performed to obtain comprehensive treatment plans. The high-risk chronic disease user is provided with each treatment plan to choose from. In this way, the health management method for the user's corresponding status is obtained.

[0041] It should be noted that the sets of various chronic disease types are constructed by statistically analyzing various chronic diseases, making it easier for doctors to make more intuitive comparisons and judgments, thereby enabling them to implement targeted and accurate chronic disease health management.

[0042] Step 3: User Chronic Disease Health Management: By monitoring chronic disease users under health management in real time, the system collects the corresponding status data of users and evaluates whether the intelligent assessment and management of chronic disease health of users corresponding to the health management system is effective.

[0043] It should be noted that by monitoring chronic disease users under health management in real time, and then collecting the corresponding status data of users, the effectiveness of the health management system in assessing the effectiveness of the chronic disease health intelligent assessment and management of users is obtained. This enables timely detection of chronic diseases, provides users with an effective chronic disease prevention platform, and efficiently protects users' physical health.

[0044] It should be noted that the physicochemical indicators include disease characteristic indicators and baseline values, such as glycated hemoglobin or blood glucose, and low-density lipoprotein; clinical symptom data include the number of attacks and tolerance values; tolerance data includes the number of adverse reactions and the number of emergency treatments. The examples given are for illustrative purposes only and are not the only limitations.

[0045] In a specific embodiment of the present invention, the evaluation obtains whether the chronic disease health intelligent assessment and management of the corresponding user of the health management system is effective. The specific evaluation process is as follows: by performing corresponding treatment monitoring on low-risk chronic disease users and high-risk chronic disease users under health management, the status data of users at each period under health management is collected, including physicochemical index data, clinical symptom data and tolerance data.

[0046] The physicochemical indicators, clinical symptoms, and tolerance data of the user at each stage of health management are denoted as β. s δ s and ρ s When (β) s ≤β′)∧(δ s ≤δ′)∧(ρ s If ≤ρ′), then the health management system is deemed to be effective in assessing and managing chronic disease health for the corresponding user. β′ is the set reference physicochemical indicator data, δ′ is the set reference clinical symptom data, ρ′ is the set reference tolerance data, and ∧ represents .

[0047] When (β) s >β′)∨(δ s >δ′)∨(ρ s If >ρ′), then the chronic disease health intelligent assessment and management of the corresponding user in the health management system is deemed invalid, and ∨ represents or.

[0048] It should be noted that when the health management system effectively assesses and manages a user's chronic disease health, it indicates that the system can promptly identify potential chronic disease risks and implement effective treatments, thereby further reducing the user's morbidity and the associated risks, and intelligently safeguarding the user's health.

[0049] It should be noted that reference physiochemical indicators, reference clinical symptoms, and reference tolerance data are set by professional physicians. These reference physiochemical indicators, reference clinical symptoms, and reference tolerance data are used to evaluate the effectiveness of the health management system's intelligent assessment and management of chronic diseases for the corresponding users, thereby enabling efficient and timely detection of users' chronic diseases and effective intelligent management of chronic diseases, and intelligently and effectively protecting users' health.

[0050] Step 4: Early Warning Prompt: An early warning prompt will be issued when the user's pre-diagnosis health status is chronic disease, the user's chronic disease status is high-risk, or the health management system's intelligent assessment and management of the user's chronic disease health is ineffective.

[0051] Please see Figure 2 As shown, a data-driven intelligent health assessment system for chronic diseases includes a user health pre-diagnosis module, a user health assessment module, a user chronic disease health management module, an early warning terminal, and a database.

[0052] The user health pre-diagnosis module is connected to the user health assessment module, the database, and the early warning terminal, respectively. The user health assessment module is connected to the user chronic disease health management module, the database, and the early warning terminal, respectively. The user chronic disease health management module is connected to the early warning terminal and the database, respectively.

[0053] The user health pre-diagnosis module is used to perform corresponding pre-health surveys on users who log in to the disease prevention and management system, thereby extracting multi-source data of the user's corresponding survey and analyzing the user's corresponding health pre-diagnosis status.

[0054] The user health assessment module is used to analyze the pre-diagnosis results of the user's corresponding health analysis, and then to obtain the set of health needs testing for the user's corresponding chronic diseases. The user can then perform the corresponding tests according to the test schedule set in the set, obtain the test indicator data of the user's corresponding test set, assess the user's status of the corresponding chronic diseases, and analyze the health management methods for the user's status.

[0055] The user chronic disease health management module is used to monitor chronic disease users under health management in real time, and then collect the corresponding status data of users to evaluate whether the intelligent assessment and management of chronic disease health of users in the health management system is effective.

[0056] The early warning terminal is used to issue early warnings when a user's pre-diagnosis health status is chronic disease, the user's chronic disease status is high-risk, or the health management system's intelligent assessment and management of the user's chronic disease health is ineffective.

[0057] The database is used to store multi-source data, reference multi-source data sets corresponding to each chronic disease, keywords for each disease, standard disease type keywords corresponding to each set of examinations, chronic disease keywords corresponding to each set of complications, examination indicator data, sets of various chronic disease types, sets of disease specialty types, and status data.

[0058] This invention, through multi-source data obtained from user surveys, analyzes and determines the user's pre-diagnosis health status. Based on this pre-diagnosis status, corresponding tests are arranged to assess the user's chronic disease status, thereby implementing targeted health management. Simultaneously, data from the managed user is collected to evaluate the effectiveness of the health management system's intelligent assessment and management of the user's chronic disease health. This achieves intelligent management and protection of the user's health, further reducing the serious risks caused by delayed chronic disease detection, enabling timely detection of chronic diseases, and addressing the shortcomings of current technologies. Furthermore, based on comprehensive user survey data, it effectively identifies users' chronic diseases, significantly improving the efficiency of chronic disease diagnosis and treatment, comprehensively and efficiently protecting users' health, enabling timely detection and management of chronic diseases, and reducing the adverse effects of chronic diseases.

[0059] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A data-driven intelligent assessment method for chronic disease health, characterized in that, include: Step 1: User Health Pre-diagnosis: By conducting a corresponding pre-health survey on users who log in to the disease prevention management system, multi-source data of the user's corresponding survey is extracted and analyzed to obtain the user's corresponding health pre-diagnosis status; Step 2, User Health Assessment: Based on the pre-diagnosis results of the user's corresponding health analysis, the system further analyzes and obtains the set of health needs tests for the user's corresponding chronic diseases. The user then performs the corresponding tests according to the test schedule set in the set, obtains the test indicator data of the user's corresponding test set, assesses the user's status of corresponding chronic diseases, and analyzes and obtains the health management methods for the user's status. Step 3: User chronic disease health management: By monitoring chronic disease users under health management in real time, the system collects the corresponding status data of users and evaluates whether the intelligent assessment and management of chronic disease health of users corresponding to the health management system is effective. Step 4: Early Warning Prompt: An early warning prompt will be issued when the user's pre-diagnosis health status is chronic disease, the user's chronic disease status is high-risk, or the health management system's intelligent assessment and management of the user's chronic disease health is ineffective.

2. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 1, characterized in that, The multi-source data includes basic data, traditional Chinese medicine data, psychological data, and other data.

3. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 2, characterized in that, The analysis yields a pre-diagnostic health status for the user, and the specific analysis process is as follows: The multi-source data corresponding to the user's survey is compared with the reference multi-source data sets corresponding to each chronic disease stored in the database. If the multi-source data corresponding to the user's survey does not overlap with any of the reference multi-source data sets corresponding to each chronic disease stored in the database, it is determined that the user does not have a chronic disease and is in a healthy state. If the multi-source data corresponding to the user's survey overlaps with the reference multi-source data set corresponding to a certain chronic disease stored in the database, it is determined that the user has a chronic disease and needs to undergo corresponding in-depth diagnosis and treatment. This analysis is used to obtain the user's corresponding pre-diagnosis status of health.

4. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 3, characterized in that, The analysis yields a set of health needs assessments for users' corresponding chronic diseases. The specific analysis process is as follows: Based on the various data contained in the multi-source survey data corresponding to users, the question and answer features corresponding to each data are extracted to form the disease keywords of each chronic disease corresponding to the user. The disease keywords of each chronic disease corresponding to the user are compared with the standard disease type keywords corresponding to the various examination sets stored in the database. If a certain disease keyword of the user corresponding to chronic disease matches the standard disease type keyword corresponding to a certain examination set stored in the database, then that examination is taken as the required examination item of the user corresponding to chronic disease. In this way, the comparison of each disease keyword is performed to obtain the required examination items of each disease keyword of the user. Based on the comprehensive composition of each required examination item, a health needs detection set is obtained. Simultaneously, based on the disease keywords of the user's corresponding chronic disease, it is compared with the chronic disease keywords corresponding to the various complication sets stored in the database to obtain the predictive concurrency set of the user's corresponding chronic disease. Then, the disease keywords corresponding to the complications in the concurrency set are extracted and compared with the standard disease type keywords corresponding to the various examination sets stored in the database to obtain the various derivative examination items under the complications. Finally, the various required examination items under the user's corresponding disease keywords are combined to form the health needs detection set. Based on the individual health need assessment set and the derivative assessment set that adds complications to the individual assessment, the corresponding health need assessment set for the user's chronic disease is analyzed, so that the user can make any selection.

5. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 4, characterized in that, The inspection indicator data includes values ​​for routine indicators, special indicators, and other indicators.

6. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 5, characterized in that, The assessment process for determining the status of a user's chronic disease is as follows: Let μ, θ, and λ represent the values ​​of regular indicators, special indicators, and other indicators under the user's corresponding detection set, respectively. If (μ < μ′) ∨ (θ < θ′) ∨ (λ < λ′), then the user's corresponding chronic disease is determined to be in a low-risk state, with a risk of chronic disease complications or malignant risk. μ′ is the set reference regular indicator value, θ′ is the set reference special indicator value, λ′ is the set reference other indicator value, and ∨ represents or. If (μ=μ′)∧(θ=θ′)∧(λ=λ′), then the user's corresponding chronic disease is determined to be in a normal state, with no risk of chronic disease mutation or malignancy, and ∧ represents the sum; If (μ>μ′)∨(θ>θ′)∨(λ>λ′), then the user's chronic disease is determined to be in a high-risk state, with the risk of chronic disease complications or malignant risks.

7. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 6, characterized in that, The analysis yields the health management method corresponding to the user's current state. The specific analysis process is as follows: When a user's chronic disease is at low risk: Based on the health test set corresponding to the low-risk chronic disease user, the corresponding chronic disease type is obtained. The chronic disease type corresponding to the low-risk chronic disease user is compared with the various chronic disease type sets stored in the database. If the chronic disease type corresponding to the low-risk chronic disease user is consistent with a certain chronic disease type set stored in the database, then the standard treatment method corresponding to that chronic disease type set is used as the health management method for the low-risk chronic disease user. When a user's chronic disease is at high risk, the chronic disease type of the high-risk chronic disease user is compared with the disease specialty set of each TCM doctor. The TCM doctors who can treat the chronic disease type of the high-risk chronic disease user are selected, and a secondary analysis of the indicator data of the health test set of each TCM doctor corresponding to the high-risk chronic disease user is performed to obtain comprehensive treatment plans. The high-risk chronic disease user is provided with each treatment plan to choose from. In this way, the health management method for the user's corresponding status is obtained.

8. The method for intelligent assessment of chronic disease health based on data analysis as described in claim 7, characterized in that, The assessment determines the effectiveness of the intelligent assessment and management of chronic disease health for the corresponding user within the health management system. The specific assessment process is as follows: By conducting corresponding treatment monitoring for low-risk and high-risk chronic disease users under health management, the system collects status data of users at various stages under health management, including physicochemical indicators, clinical symptoms, and tolerance data. The physicochemical indicators, clinical symptoms, and tolerance data of the user at each stage of health management are denoted as β. s δ s and ρ s When (β) s ≤β′)∧(δ s ≤δ′)∧(ρ s If ≤ρ′), then the health management system is deemed to be effective in assessing and managing chronic disease health for the corresponding user. β′ is the set reference physicochemical indicator data, δ′ is the set reference clinical symptom data, ρ′ is the set reference tolerance data, and ∧ represents the sum. When (β) s >β′)∨(δ s >δ′)∨(ρ s If >ρ′), then the chronic disease health intelligent assessment and management of the corresponding user in the health management system is deemed invalid, and ∨ represents or.

9. A chronic disease health intelligent assessment system that implements the data analysis-based chronic disease health intelligent assessment method according to any one of claims 1-8, characterized in that, include: The user health pre-diagnosis module is used to perform corresponding pre-health surveys on users who log in to the disease prevention and management system, thereby extracting multi-source data of the user's corresponding survey and analyzing the user's corresponding health pre-diagnosis status. The user health assessment module is used to analyze the pre-diagnosis results of the user's corresponding health analysis, and then analyze the set of health needs testing for the user's corresponding chronic diseases. The user can then perform the corresponding tests based on the test schedule set in the set, obtain the test indicator data of the user's corresponding test set, assess the user's status of the corresponding chronic diseases, and analyze the health management methods for the user's status. The user chronic disease health management module is used to monitor chronic disease users under health management in real time, and then collect the corresponding status data of users to evaluate whether the intelligent assessment and management of chronic disease health of users in the health management system is effective. The early warning terminal is used to issue early warnings when a user's pre-diagnosis health status is chronic disease, the user's chronic disease status is high-risk, or the health management system's intelligent assessment and management of the user's chronic disease health is ineffective.

10. The chronic disease health intelligent assessment system based on data analysis as described in claim 9, characterized in that, It also includes a database, which stores multi-source data, reference multi-source data sets corresponding to each chronic disease, keywords for each disease, standard disease type keywords corresponding to each set of examinations, chronic disease keywords corresponding to each set of complications, examination indicator data, sets of various chronic disease types, sets of disease specialty types, and status data.

Images