A cloud platform-based traditional Chinese medicine chronic disease home nursing method

Abstract

The application discloses a traditional Chinese medicine chronic disease family nursing method based on a cloud platform, relates to the technical field of intelligent health services, and comprises the following steps: performing deep fusion and intelligent analysis on a family nursing data package by constructing a virtual patient model, generating personalized data of patient physiological indexes and traditional Chinese medicine syndrome states, generating a customized family nursing candidate scheme based on the personalized data of the patient physiological indexes and the traditional Chinese medicine syndrome states, combining behavior prediction analysis, intelligently evaluating and real-time feeding back, and forming a traditional Chinese medicine chronic disease family nursing management scheme according to a nursing scheme set, combining physiological index and symptom data analysis correction. The application can accurately reflect the current health state of a patient by collecting physiological data and traditional Chinese medicine syndrome information of the patient, combining family environment data, constructing a dynamically updated virtual patient model, and realizing the personalization and dynamic adaptation of a nursing scheme.

Description

Technical Field

[0001] This invention relates to the field of intelligent health service technology, and in particular to a cloud-based method for home care of chronic diseases using traditional Chinese medicine. Background Technology

[0002] With the development of intelligent health service technology, cloud-based intelligent health management has gradually become an important direction in the field of chronic disease care. In recent years, cloud computing, artificial intelligence, and Internet of Things technologies have been widely applied in health management systems, promoting the realization of personalized health management. Building virtual patient models by collecting and analyzing physiological data, lifestyle habits, and family environment information of chronic disease patients has become a research hotspot. This not only helps to monitor patients' health status in real time but also generates personalized care plans based on patients' needs, improving the accuracy and efficiency of health management.

[0003] However, existing cloud-based health management methods still face some challenges, particularly in matching and dynamically adjusting care plans for patients with chronic diseases. Care plan generation is often based on static patient data, failing to fully consider the temporal changes in patient health status and the dynamic impact of the living environment; and how to dynamically adjust care plans based on real-time physiological indicators and symptom data to improve care outcomes remains a challenge. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a cloud-based home care method for chronic diseases using traditional Chinese medicine, which solves the problem of dynamically adjusting care plans based on real-time health status.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: A cloud-based method for home-based care of chronic diseases using traditional Chinese medicine (TCM) includes: collecting and uploading information on chronic diseases and the home environment; processing this information using a decision tree algorithm to obtain a home care data package for each patient; deeply integrating and intelligently analyzing the home care data package by constructing a virtual patient model to generate personalized data on the patient's physiological indicators and TCM syndrome status; generating customized home care candidate plans based on the personalized data of the patient's physiological indicators and TCM syndrome status, combined with behavioral prediction analysis, intelligent assessment, and real-time feedback; simulating and analyzing the home care candidate plans using simulation data analysis to generate a structured evaluation result set for each plan; adjusting the adaptability of each plan based on the structured evaluation result set using a genetic algorithm to ensure the plan matches individual needs, resulting in a set of care plans; and finally, based on the set of care plans, analyzing and correcting them using physiological indicators and symptom data to form a TCM-based home care management plan for chronic diseases.

[0006] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the collected and uploaded information on chronic diseases and home environment is processed using a decision tree algorithm to obtain a home care data package for a single patient. The specific steps are as follows: Information on chronic diseases and home environments collected from the cloud platform is cleaned and standardized to obtain a complete dataset for each patient. Based on the complete dataset, a decision tree algorithm is used to filter and process the patient's chronic disease status and family environmental factors to generate a family care data package for the patient.

[0007] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the virtual patient model is constructed as follows: A virtual patient model is constructed based on a data acquisition layer, an analysis and extraction layer, and a demand feedback layer. The data acquisition layer, based on the patient's uploaded data on chronic diseases, physical condition, symptoms, and family environment, integrates various information to obtain a preliminary description of the patient's health status. The analysis and extraction layer identifies the main characteristics of the patient's current physiological indicators and TCM syndromes by analyzing and integrating the preliminary health status description, and extracts the patient's health characteristics. The demand feedback layer, based on the extracted health characteristics of the patient, assesses the patient's nursing needs, optimizes and adjusts the nursing plan, and generates information reflecting the patient's current physiological indicators and TCM syndrome status.

[0008] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the home care data package refers to the patient's basic information, chronic disease history, lifestyle habits, and living environment data.

[0009] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the specific steps for generating personalized data on patients' physiological indicators and TCM syndrome states are as follows: Based on patients' chronic disease data and home environment information, a cross-modal context alignment method is used to deeply fuse home care data packages to obtain a health status tensor. Based on the health status tensor, combined with the patient's physiological indicators and environmental changes, the TCM syndrome status is intelligently analyzed to generate personalized data on the patient's physiological indicators and TCM syndrome status.

[0010] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the method generates customized home care candidate plans based on personalized data of patients' physiological indicators and TCM syndrome states, combined with behavioral prediction analysis, intelligent assessment, and real-time feedback. The specific steps are as follows: Based on personalized data of patients' physiological indicators and TCM syndrome status, behavioral predictive analysis is used to couple and correlate chronic disease history with TCM syndrome status to obtain a dynamic behavioral profile that reflects the synergistic changes in individual behavioral preferences and health status. Based on dynamic behavioral profiles, multi-dimensional analysis is used to conduct contextual intelligent assessment of patients' current physiological indicators and TCM syndrome status, integrate individual response tendencies for real-time feedback, and generate customized home care candidate plans.

[0011] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the method employs simulation data analysis to simulate and analyze customized home care candidate solutions, generating a structured evaluation result set for each solution. The specific steps are as follows: Based on simulation data analysis, dynamic simulations of customized home care candidate solutions are conducted to evaluate their adaptability and effectiveness under different environments and situations, and to obtain nursing data for each solution. Multi-dimensional analysis of nursing data from each plan was conducted to extract physiological indicators and potential risks associated with the practical application of candidate home care plans. Based on physiological indicators and potential risks, the evaluation effect of each scheme in practical application is simulated and analyzed using simulation data analysis method, generating a structured evaluation result set.

[0012] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the method involves using a genetic algorithm to screen and adjust the adaptability of each plan based on a structured evaluation result set, ensuring that the plans match individual needs, and obtaining a set of care plans. The specific steps are as follows: Based on the structured evaluation results set, the adaptability of each nursing plan is classified to obtain the nursing needs characteristics of different patient groups; Adaptability analysis and evaluation were conducted on nursing needs characteristics across different dimensions to obtain the degree of matching between each plan and patient needs, and to assess the adaptability of each plan to patient needs. Based on the adaptability of each plan to the patient's needs, a genetic algorithm is used to optimize the suitability of each nursing plan, resulting in a set of suitable nursing plans.

[0013] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the physiological indicators and symptom data refer to the patient's health data such as blood pressure, blood sugar, and heart rate transmitted back through the home terminal, as well as the patient's subjective reports of symptom changes and physical reactions.

[0014] As a preferred embodiment of the cloud-based home care method for chronic diseases using traditional Chinese medicine, the specific steps for forming a home care management plan for chronic diseases using traditional Chinese medicine, based on a set of care plans and combined with physiological indicators and symptom data analysis and correction, are as follows: Based on physiological indicators and symptom data, information analysis and evaluation of patients' health status and nursing effects are conducted to identify nursing procedures that need to be optimized. Genetic algorithms are used to dynamically correct nursing procedures that need to be optimized, adjusting the intensity, frequency, and method of treatment to obtain a nursing care plan that meets the patient's needs. Based on the patient's nursing needs, the nursing plan and the feedback data are continuously adjusted and corrected to form a home care management plan for chronic diseases using traditional Chinese medicine.

[0015] The beneficial effects of this invention are as follows: By collecting patients' physiological data and TCM syndrome information, combined with family environment data, a dynamically updated virtual patient model is constructed, which accurately reflects the patient's current health status and realizes the personalization and dynamic adaptation of nursing plans; by using simulation data analysis, the adaptability of each nursing candidate plan under different environments and situations can be evaluated through simulation, which can optimize nursing plans in real time while providing personalized chronic disease nursing management, improve patients' treatment effects and quality of life, and significantly improve the individual adaptability and implementation reliability of TCM family nursing. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. 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.

[0017] Figure 1 This is a flowchart of a cloud-based home care method for chronic diseases using traditional Chinese medicine.

[0018] Figure 2 A flowchart for data acquisition and model building.

[0019] Figure 3 A flowchart for generating analysis of nursing plans.

[0020] Figure 4 A flowchart for the development of a home care management plan. Detailed Implementation

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0023] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0024] Reference Figures 1-4 This is one embodiment of the present invention, which provides a cloud-based home care method for chronic diseases using traditional Chinese medicine, comprising the following steps: S1: Collect and upload information on chronic diseases and home environment, and process it through a decision tree algorithm to obtain a home care data package for a single patient.

[0025] S1.1: Clean and standardize the chronic disease and home environment information collected based on the cloud platform to obtain a complete dataset for each patient.

[0026] Furthermore, the chronic disease and home environment information collected from the cloud platform is cleaned to remove invalid and duplicate data, and various types of data are uniformly formatted to ensure data consistency and accuracy. Through standardization, data from different sources are unified to the same metric. The cleaned and standardized data are then filtered and classified according to the patient's chronic disease history, lifestyle habits, and living environment factors to obtain a complete dataset for each patient.

[0027] Specifically, measurement standards refer to the unified units, ranges, and specifications set for different types of data (blood pressure and blood sugar) during the data processing process, so that different types of data can be compared and analyzed within the same framework.

[0028] Environmental factors refer to external conditions that affect a patient's health, including living environment, health status of family members, lifestyle, dietary habits, and air quality.

[0029] Uniform formatting refers to converting patient data from different sources into a unified standard format, including standardization of data types, units, and structures, to ensure the consistency and comparability of patient data.

[0030] S1.2 Based on the complete dataset, the patient's chronic disease status and family environment factors are filtered using a decision tree algorithm to generate a family care data package for the patient.

[0031] Furthermore, by analyzing and integrating information from the complete dataset, nursing data related to patient health is identified, and decision tree algorithms are used to filter and process the patient's chronic disease status and family environmental factors to identify features that have an impact on the patient's health, thereby generating a family care data package for the patient.

[0032] It should be noted that decision tree algorithm screening refers to processing patients' chronic disease status and family environmental factors through data analysis to extract characteristics related to the patient's health (patient's chronic disease status, lifestyle habits, physical condition and family environment data).

[0033] The patient's chronic disease status and family environmental factors refer to the patient's chronic disease type, medical history, lifestyle habits, physical condition, and the environmental conditions of their family. The environmental conditions of the family include factors that affect the patient's health, such as living conditions, the health status of family members, and lifestyle.

[0034] S2: By constructing a virtual patient model, the family care data package is deeply integrated and intelligently analyzed to generate personalized data on the patient's physiological indicators and TCM syndrome status; the virtual patient model is constructed based on the data acquisition layer, analysis and extraction layer, and demand feedback layer.

[0035] S2.1: Data Acquisition Layer. Based on the patient's uploaded data on chronic diseases, physical condition, symptoms, and family environment, the layer integrates various information to obtain a preliminary description of the patient's health status.

[0036] Furthermore, based on the patient's uploaded data on chronic diseases, physical condition, symptoms, and family environment, the data is integrated, and the information is categorized and organized to obtain a preliminary description of the patient's health status. Based on the preliminary health data, the patient's physiological condition and living environment are analyzed and evaluated to generate preliminary health status information, providing data support for the analysis and extraction layer.

[0037] S2.2: Analysis and extraction layer. By analyzing and integrating the preliminary health status description, the main characteristics of the patient's current physiological indicators and TCM syndrome are identified, and the patient's health characteristics are extracted.

[0038] Furthermore, based on the preliminary health status description, the main physiological indicators and TCM syndrome characteristics affecting the patient's health are identified by analyzing and integrating the patient data. Based on the main physiological indicators and TCM syndrome characteristics, health characteristic factors related to the patient are extracted to generate a detailed description of the patient's current health status, providing data support for the demand feedback layer.

[0039] S2.3: Needs Feedback Layer. Based on the extracted health characteristics of the patient, the nursing needs of the patient are assessed, the nursing plan is optimized and adjusted, and information reflecting the patient's current physiological indicators and TCM syndrome status is generated.

[0040] Furthermore, based on the extracted health characteristics of the patients, a suitability score for personalized nursing recommendations is generated. By optimizing and adjusting the suitability score of the nursing recommendations, information reflecting the current physiological indicators and TCM syndrome status of the patients is generated.

[0041] Specifically, optimization and adjustment involves generating a personalized care plan based on the patient's health characteristics and needs analysis. This includes adjustments to the treatment plan, lifestyle recommendations, and symptom management strategies, thereby optimizing the care plan to meet the patient's needs.

[0042] The formula for assessing the suitability of the nursing care plan is as follows: ; in, The fit score represents the degree to which each care plan matches the patient's needs (the range depends on the specific health data item). The value and the corresponding weight ), Indicates the first Health data (blood pressure and blood sugar). Indicates the patient's first Health data (physiological data changes in blood pressure, blood sugar, and heart rate). It is the total number of health data items in the assessment. These represent different health data (blood pressure, blood sugar, and heart rate).

[0043] The training process of a virtual patient model includes data acquisition, feature extraction, model training, and calibration.

[0044] By collecting patients' chronic disease history, physical condition, symptoms, and family environment information, and performing data cleaning and standardization, the accuracy and consistency of home care data are ensured. Physiological indicators and TCM syndrome characteristics of patients are extracted from the home care data to construct a preliminary health status description. This preliminary health status description is then used to train a virtual patient model. Through continuous adjustment and optimization, the model predicts and assesses the patient's health status. Finally, the model is corrected by combining the patient's subjective symptom records and health change trends. Through the training process of the virtual patient model, information reflecting the patient's current physiological indicators and TCM syndrome status is obtained.

[0045] Specifically, subjective symptom records refer to detailed records of patients' self-reported physical discomfort, symptom changes, and feelings, which can help assess the patient's health status.

[0046] S2.4: Home care data package refers to the patient's basic information, chronic disease history, lifestyle habits and living environment data.

[0047] S2.5: Based on the patient's chronic disease data and home environment information, a cross-modal context alignment method is used to deeply fuse the home care data package to obtain the health status tensor.

[0048] Furthermore, physiological records (physiological health data, referring to health indicators such as blood pressure, blood sugar, and heart rate) in chronic disease data are aligned with temperature, humidity, light, air quality, and environmental parameters in home environment information according to timestamps and event contexts. Cross-modal context alignment methods are used to deeply fuse data from different sources at the semantic level, integrating abnormal physiological fluctuations with environmental changes to obtain a health state tensor that represents physiological state, syndrome tendencies, and environmental influences.

[0049] It should be noted that cross-modal context alignment refers to the deep fusion of data from different sources and modalities (patients' chronic disease data, family environment information, and behavioral data) to work together in a unified context to achieve information complementarity and enhancement. Cross-modal context alignment analyzes the correlation between chronic disease data and family environment information, identifies and aligns similarities in time, space, and context, eliminates heterogeneity between data, and obtains the integration of information from different modalities within the same framework.

[0050] The semantic-level deep fusion process includes data cleaning and unified formatting, feature extraction and alignment, and health state tensor generation.

[0051] Data cleaning and standardized formatting are performed on patient data (physiological data, chronic disease history, lifestyle and environmental data) from different sources.

[0052] Feature extraction and alignment: At the semantic level, a cross-modal context alignment method is used to analyze and align data from different modalities. Physiological data, behavioral data, environmental data, and TCM syndrome status information are integrated into the same semantic framework by identifying various types of data (blood pressure, blood sugar, and environmental factors).

[0053] The health status tensor is generated, and the deeply fused data will be transformed into a health status tensor, which reflects the patient's physiological status and health information of the living environment.

[0054] S2.6: Based on the health status tensor, combined with the patient's physiological indicators and environmental changes, intelligent analysis of TCM syndrome status is performed to generate personalized data of the patient's physiological indicators and TCM syndrome status.

[0055] Furthermore, by utilizing the physiological state and health information of the living environment in the health status tensor, a cross-modal context alignment method is used to intelligently analyze the TCM syndrome status and modern physiological observation content, obtaining the distribution of TCM syndrome characteristics reflecting the interaction between internal and external environments. Based on the distribution of TCM syndrome characteristics, behavioral prediction analysis is provided to intelligently analyze the patient's physiological indicators and environmental changes, obtaining a TCM syndrome status description that is coordinated with the temporal changes of the patient's physiological indicators, and generating personalized data of the patient's physiological indicators and TCM syndrome status.

[0056] Specifically, physiological indicators refer to the physical health status reflected by a patient's blood pressure, blood sugar, and heart rate, and are used to assess the patient's physiological state.

[0057] Traditional Chinese medicine syndrome characteristics refer to the types of syndromes derived from the analysis of a patient's constitution, symptoms, and medical history based on traditional Chinese medicine theory, reflecting the patient's internal health status and pathological changes.

[0058] The intelligent analysis process includes data cleaning and uniform formatting, feature extraction and cross-modal alignment, and intelligent analysis and personalized data generation.

[0059] Data cleaning and standardized formatting are performed on the collected chronic disease and home environment information to remove noise, invalid and duplicate data. Different types of data (blood pressure, blood sugar, heart rate and home environment parameters) are standardized to ensure data consistency.

[0060] Feature extraction and cross-modal alignment: A cross-modal context alignment method is used to extract and align features from different data sources (physiological data, family environment and behavioral data). By analyzing the different environments and contexts of the data sources, the heterogeneity between different data sources is eliminated and integrated into a unified framework.

[0061] Intelligent analysis and personalized data generation, based on the health status tensor, combined with the patient's physiological indicators and environmental changes, extracts the influence of TCM syndrome state-environment interaction on TCM syndrome, and generates TCM syndrome characteristics that match the patient's physiological state.

[0062] It should be noted that personalized data refers to health data that reflects the health status of each patient, generated through intelligent analysis and deep fusion processing based on the patient's physiological indicators, TCM syndrome status, and health information of their living environment.

[0063] Modern physiological observation refers to the continuous monitoring and analysis of a patient's physiological data, such as health parameters like blood pressure, blood sugar, and heart rate. This physiological data is collected via sensors and medical devices and uploaded to a cloud platform for processing and evaluation. By tracking changes in physiological indicators in real time, the patient's health status is assessed, providing foundational data support for personalized home care plans.

[0064] Traditional Chinese medicine syndrome elements refer to the analysis of a patient's physiological state, symptoms, constitution, and environmental factors to extract various characteristics related to the patient's current health status and reflect the patient's TCM syndrome state.

[0065] By combining patients' chronic disease data and family environment information, we analyze and extract factors that affect health, such as physiological indicators, symptoms, and constitution types, and identify and analyze them to obtain the patient's TCM syndrome status.

[0066] S3: Based on personalized data of patients' physiological indicators and TCM syndrome status, combined with behavioral prediction analysis, intelligent assessment and real-time feedback, customized home care candidate plans are generated.

[0067] S3.1: Based on personalized data of patients' physiological indicators and TCM syndrome status, behavioral predictive analysis is used to couple and correlate chronic disease history with TCM syndrome status to obtain a dynamic behavioral profile that reflects the synergistic changes in individual behavioral preferences and health status.

[0068] Furthermore, based on personalized data of patients' physiological indicators and TCM syndrome status, behavioral predictive analysis is used to couple and correlate the changes (improvement and deterioration) of patients' chronic disease history and TCM syndrome status over time. By identifying individual behavioral preferences and health status between behavioral events and syndrome changes, a dynamic behavioral profile reflecting the synergistic changes of individual behavioral preferences and health status is obtained.

[0069] Specifically, TCM syndrome information refers to indicators reflecting health status collected from a patient's constitution, symptoms, and tongue and pulse characteristics based on TCM theory.

[0070] Coupling association analysis refers to the in-depth analysis of patients' chronic disease history and family environment data to obtain the changes between behavioral events (lifestyle habits and environmental changes) and changes in TCM syndromes, revealing the synergistic changes in an individual's health status and behavioral preferences.

[0071] S3.2: Based on dynamic behavioral profiles, use multi-dimensional analysis to conduct contextual intelligent assessment of the patient's current physiological indicators and TCM syndrome status, integrate and provide real-time feedback on individual response tendencies, and generate customized home care candidate plans.

[0072] Furthermore, based on the dynamic behavioral profile, multi-dimensional analysis is used to conduct contextual intelligent assessment of the patient's current physiological indicators and TCM syndrome status (combining the patient's physiological indicators, TCM syndrome status, and real-time feedback data to analyze and assess the patient's health status). By analyzing the characteristics of the synergistic changes in individual behavioral preferences and health status contained in the dynamic behavioral profile, and combining personalized data of the patient's physiological indicators and TCM syndrome status, nursing intervention directions that match the current health status are identified, and nursing needs values ​​corresponding to the intervention strategies are determined.

[0073] The study uses a multi-objective model to extrapolate the expected effects of each patient's current physiological indicators and TCM syndrome status under different life situations, and evaluates the comprehensive performance in three dimensions: behavioral compliance, syndrome improvement potential, and physiological indicator regulation ability. It integrates and provides real-time feedback on individual response tendencies, and coordinates the patient's response to intervention measures in historical behavioral trajectories with the current extrapolation results and nursing needs values ​​to dynamically adjust the composition and intensity of each nursing intervention strategy and generate customized home care candidate plans.

[0074] The patient's nursing needs are expressed as follows: ; in, This represents the patient's nursing needs. This represents the bias term (usually in the range of real numbers).

[0075] It should be noted that multidimensional analysis refers to the process of comprehensively considering the optimization needs of multiple nursing goals during the generation of personalized care plans, and making adjustments based on multidimensional data on the patient's health status, lifestyle habits, and behavioral preferences.

[0076] The patient's current physiological indicators and TCM syndrome status refer to the nursing intervention plan proposed based on the analysis of the patient's health data, individual needs, and behavioral predictions. By comprehensively evaluating the patient's physiological indicators, symptom changes, TCM syndrome status, and lifestyle habits from multiple dimensions, intervention measures suitable for the patient's current health status are identified.

[0077] S4: Using simulation data analysis, simulate and analyze customized home care candidate solutions to generate a structured evaluation result set for each solution.

[0078] S4.1: Based on simulation data analysis, dynamic simulations are performed on customized home care candidate plans to evaluate their adaptability and effectiveness under different environments and situations, and to obtain nursing data for each plan.

[0079] Furthermore, based on simulation data analysis, dynamic simulations of customized home care candidate plans are conducted. Patient physiological data and TCM syndrome information are used to simulate nursing plans in multiple scenarios, evaluate the adaptability and effectiveness of each plan in different environments and situations, and extract the performance indicators and potential risks of each plan by performing multi-dimensional analysis on the data generated by each plan during the simulation process. By analyzing the feasibility and effectiveness in practical applications, nursing data for each plan is obtained.

[0080] Specifically, simulation data analysis refers to evaluating the adaptability and effectiveness of nursing plans by simulating the health status of patients in different environments and situations, and optimizing the implementation effect of the plan by analyzing performance indicators and potential risks.

[0081] Performance indicators refer to the effectiveness and efficiency of the nursing plan in actual application, while potential risks refer to factors that lead to adverse reactions and effects (variables that affect the patient's health status during the implementation of the nursing plan, including treatment intensity, frequency, patient compliance, environmental changes, and side effects).

[0082] Dynamic simulation refers to evaluating the adaptability, effectiveness, and performance in practical applications of nursing plans by simulating the implementation of nursing plans under different environments and situations.

[0083] S4.2: Conduct multi-dimensional analysis of nursing data for each plan to extract physiological indicators and potential risks of candidate home care plans in practical application.

[0084] Furthermore, the nursing data of each plan is analyzed from multiple dimensions. By analyzing the nursing data of each plan under different environments and situations, the indicators and potential risk factors affecting the effectiveness of home care are extracted. In the process of analysis, the patient's physiological indicators and symptom changes are combined to identify the risks and shortcomings of each plan in practical application. The plan is then optimized through data analysis and processing, and the resulting nursing plan can meet the patient's needs and reduce potential risks.

[0085] It should be noted that multidimensional analysis refers to a comprehensive evaluation of multiple performance indicators of a nursing care program, covering aspects such as efficacy, safety, compliance, and cost, to identify the main analytical methods affecting nursing outcomes.

[0086] S4.3: Based on physiological indicators and potential risks, the evaluation effect of each scheme in practical application is simulated and analyzed using simulation data analysis method to generate a structured evaluation result set.

[0087] Furthermore, based on indicators and potential risks, the evaluation effect of each plan in practical application is simulated and analyzed using simulation data analysis. The adaptability and effectiveness of each family care candidate plan under different environments and situations are evaluated through dynamic simulation (based on dynamic simulation). Nursing data generated by each plan in practical application are collected, and the nursing data is analyzed in multiple dimensions to extract the main indicators and potential risks of each plan, as well as the responses to different nursing needs and environmental changes. Based on the indicators and potential risks, a comprehensive analysis of each plan is conducted to generate a structured evaluation result set.

[0088] Specifically, nursing needs and environmental changes refer to the dynamic changes in a patient's health status, symptoms, lifestyle habits, and living environment factors.

[0089] S5: Based on the structured evaluation result set, the adaptability of each plan is screened and adjusted through a genetic algorithm to ensure that the plan matches individual needs, thus obtaining a set of nursing plans.

[0090] S5.1: Based on the structured evaluation results set, classify the adaptability of each nursing plan to obtain the nursing needs characteristics of different patient groups.

[0091] Furthermore, the nursing needs characteristics of different patient groups are extracted. Based on various health statuses, chronic disease types, and environmental factors, the applicability of each plan is subdivided. Through multi-dimensional adaptability analysis of nursing needs characteristics, the degree of matching between each plan and patient needs is evaluated. The effectiveness and relevance of each nursing plan in different patient groups are assessed. Combining the health characteristics and needs differences of each group, the adaptability of the nursing plan is optimized and classified to obtain the nursing needs characteristics of different patient groups.

[0092] It should be noted that nursing needs characteristics refer to nursing data and features that reflect the individualized nursing needs of patients, extracted based on their health status, type of chronic disease, lifestyle habits, and family environment factors.

[0093] The scope of application is determined by analyzing multidimensional data on the patient's health status, type of chronic disease, lifestyle habits, and family environment. The subdivision of the scope of application is actually a dynamic adjustment and optimization based on the patient's personalized needs, and no fixed value is set.

[0094] The degree of matching of needs refers to the suitability and consistency between the nursing plan and the patient's individual health needs; by analyzing the patient's health data, the degree to which each nursing plan conforms to the patient's actual needs in terms of treatment intensity, frequency and method is evaluated.

[0095] For example, a patient's health data includes physiological indicators such as blood pressure, blood sugar, and heart rate. The nursing plan is selected through genetic algorithms. The nursing plan measures are flexibly adjusted according to the patient's different physiological conditions and symptoms to meet personalized health needs.

[0096] S5.2: Conduct adaptability analysis and evaluation on different dimensions of nursing needs characteristics to obtain the degree of matching between each plan and patient needs, and evaluate the adaptability of each plan to patient needs.

[0097] Furthermore, based on patients' physiological data and TCM syndrome status, the applicability of the treatment intensity, frequency, and methods of each nursing plan is evaluated, the response of different patient groups to the plan is analyzed, and by analyzing the characteristics of different nursing needs and the degree of need of patients' health status, the health management effect plan for patients is gradually optimized and adjusted, the degree of matching between each plan and patients' needs is obtained, and the adaptability of each plan to patients' needs is evaluated.

[0098] Specifically, response status refers to assessing the suitability and effectiveness of each nursing plan in terms of treatment intensity, frequency, and methods, based on the patient's health condition and individual needs.

[0099] S5.3: Based on the adaptability of each plan to the patient's needs, a genetic algorithm is used to optimize the suitability of each nursing plan, resulting in a set of suitable nursing plans.

[0100] Furthermore, based on the degree of matching between each nursing plan and the patient's needs, the adaptability of each plan under different environments and situations is analyzed. Through genetic algorithm methods, the adaptability of each nursing plan is optimized, and the nursing data of the plan is gradually adjusted to meet the patient's personalized needs. After optimization, a set of suitable nursing plans is generated.

[0101] It should be noted that genetic algorithms are algorithms that optimize nursing plans by simulating natural selection and genetic mechanisms. Through continuous iteration and screening, more adaptable plans are selected to provide plans that better meet the individualized needs of patients.

[0102] S6: Based on the set of nursing plans, combined with physiological indicators and symptom data analysis and correction, a traditional Chinese medicine home care management plan for chronic diseases is formed.

[0103] S6.1: Physiological indicators and symptom data refer to the patient's health data such as blood pressure, blood sugar, and heart rate transmitted back through the home terminal, as well as the patient's subjective reports of symptom changes and physical reactions.

[0104] S6.2: Based on physiological indicators and symptom data, conduct information analysis and evaluation on the patient's health status and nursing effectiveness, and identify nursing procedures that need to be optimized.

[0105] Furthermore, by collecting physiological data such as blood pressure, blood sugar, and heart rate from patients, as well as subjective reports of symptom changes from patients, we can analyze the changing trends of various health indicators and symptom responses, identify deficiencies in the nursing process, and identify nursing procedures that need to be optimized through multi-dimensional analysis of patients' health status and nursing effects.

[0106] Specifically, subjective reports refer to health information provided by patients based on their own feelings and changes in symptoms.

[0107] Identifying deficiencies in the nursing process involves analyzing changes in the patient's physiological indicators and symptoms to identify the need for adjustments in treatment intensity, frequency, and methods.

[0108] S6.3: Use genetic algorithms to dynamically correct the nursing procedures to be optimized, adjust the intensity, frequency and method of treatment, and obtain the nursing needs plan for the patient.

[0109] Furthermore, when using genetic algorithms to dynamically correct nursing procedures to be optimized, the shortcomings in the current nursing plan are identified by real-time analysis of the returned physiological indicators and symptom data. Based on patient feedback, changes in health status, and the evolution of TCM syndromes, the treatment intensity, frequency, and methods in the nursing plan are dynamically corrected to match the patient's actual needs, thus obtaining the patient's nursing needs plan.

[0110] Ideally, during the adjustment process, the nursing care process should be continuously optimized by combining the patient's individual needs information, so that the treatment plan can remain flexible during implementation, respond promptly to changes in the patient's health, and form a nursing care plan that meets the patient's needs.

[0111] Specifically, dynamic correction refers to adjusting the intensity, frequency, and method of treatment in the nursing plan based on the patient's real-time physiological data and symptom changes, so that the nursing plan can continuously adapt to the patient's individual needs.

[0112] Nursing needs planning refers to a personalized nursing plan generated based on the patient's physiological state, TCM syndrome information, and health status analysis results. This plan includes the intensity, frequency, and method of treatment to meet the patient's specific health needs.

[0113] S6.4: Based on the patient's nursing needs, continuously adjust and correct the nursing plan and the feedback data to form a home nursing management plan for chronic diseases using traditional Chinese medicine.

[0114] Furthermore, based on the patient's nursing needs, and combined with physiological indicators and symptom data, continuous analysis and correction are performed. In response to changes in the patient's health shown in the returned data, the treatment intensity, frequency, and method of the nursing plan are adjusted in real time. The nursing plan can be flexibly adapted to changes in the patient's health status through genetic algorithms, forming a traditional Chinese medicine home care management plan for chronic diseases.

[0115] The best approach is to achieve personalized and continuously optimized nursing outcomes. The combination of nursing plans and feedback data ensures that every intervention measure can accurately match the patient's actual health needs.

[0116] It should be noted that the home care management plan refers to a personalized TCM chronic disease care plan that is dynamically adjusted and optimized based on the patient's health status, care needs, and feedback data.

[0117] The nursing plan includes a personalized care plan for the patient, which specifically includes adjustments to the intensity, frequency and method of treatment, combined with traditional Chinese medicine treatment methods, lifestyle recommendations, medication use, symptom management and continuous monitoring and feedback of the patient's health status.

[0118] In summary, this invention constructs a dynamically updated virtual patient model by collecting patients' physiological data and TCM syndrome information, combined with family environment data, to accurately reflect the patient's current health status and achieve personalized and dynamic adaptation of nursing plans. Simulation data analysis is used to evaluate the adaptability of each nursing candidate plan under different environments and situations. While providing personalized chronic disease nursing management, it can optimize nursing plans in real time, improving patients' treatment outcomes and quality of life, and significantly enhancing the individual adaptability and reliability of TCM home nursing.

[0119] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A cloud-based home care method for chronic diseases using traditional Chinese medicine, characterized in that, include: Information on chronic diseases and home environments is collected and uploaded, and then filtered and processed using a decision tree algorithm to obtain a home care data package for each individual patient. By constructing a virtual patient model, the data package of home care is deeply integrated and intelligently analyzed to automatically generate personalized data on the patient's physiological indicators and TCM syndrome status. Based on personalized data of patients' physiological indicators and TCM syndrome status, combined with behavioral predictive analysis, intelligent assessment and real-time feedback, customized home care candidate plans are generated. Using simulation data analysis, candidate home care solutions are simulated and analyzed to generate a structured evaluation result set for each solution; Based on the structured evaluation result set, the adaptability of each plan is screened and adjusted through a genetic algorithm to ensure that the plan matches individual needs, thus obtaining a set of nursing plans. Based on the set of nursing plans, combined with physiological indicators and symptom data analysis and correction, a home care management plan for chronic diseases using traditional Chinese medicine was developed.

2. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 1, characterized in that, The collected and uploaded information on chronic diseases and home environments is processed using a decision tree algorithm to obtain a home care data package for each patient. The specific steps are as follows: Information on chronic diseases and home environments collected from the cloud platform is cleaned and standardized to obtain a complete dataset for each patient. Based on the complete dataset, a decision tree algorithm is used to filter and process the patient's chronic disease status and family environmental factors to generate a family care data package for the patient.

3. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 2, characterized in that, The virtual patient model is constructed as follows: A virtual patient model is constructed based on a data acquisition layer, an analysis and extraction layer, and a demand feedback layer. The data acquisition layer, based on the patient's uploaded data on chronic diseases, physical condition, symptoms, and family environment, integrates various information to obtain a preliminary description of the patient's health status. The analysis and extraction layer identifies the main characteristics of the patient's current physiological indicators and TCM syndromes by analyzing and integrating the preliminary health status description, and extracts the patient's health characteristics. The demand feedback layer, based on the extracted health characteristics of the patient, assesses the patient's nursing needs, optimizes and adjusts the nursing plan, and generates information reflecting the patient's current physiological indicators and TCM syndrome status.

4. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 3, characterized in that, The home care data package refers to the patient's basic information, chronic disease history, lifestyle habits, and living environment data.

5. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 4, characterized in that, The specific steps for generating personalized data on patients' physiological indicators and TCM syndrome states are as follows: Based on patients' chronic disease data and home environment information, a cross-modal context alignment method is used to deeply fuse home care data packages to obtain a health status tensor. Based on the health status tensor, combined with the patient's physiological indicators and environmental changes, the TCM syndrome status is intelligently analyzed to generate personalized data on the patient's physiological indicators and TCM syndrome status.

6. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 5, characterized in that, The personalized data based on patients' physiological indicators and TCM syndrome states, combined with behavioral predictive analysis, intelligent assessment, and real-time feedback, generates customized home care candidate plans. The specific steps are as follows: Based on personalized data of patients' physiological indicators and TCM syndrome status, behavioral predictive analysis is used to couple and correlate chronic disease history with TCM syndrome status to obtain a dynamic behavioral profile that reflects the synergistic changes in individual behavioral preferences and health status. Based on dynamic behavioral profiles, multi-dimensional analysis is used to conduct contextual intelligent assessment of patients' current physiological indicators and TCM syndrome status, integrate individual response tendencies for real-time feedback, and generate customized home care candidate plans.

7. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 6, characterized in that, The method of using simulation data analysis to simulate and analyze customized home care candidate solutions generates a structured evaluation result set for each solution. The specific steps are as follows: Based on simulation data analysis, dynamic simulations of customized home care candidate solutions are conducted to evaluate their adaptability and effectiveness under different environments and situations, and to obtain nursing data for each solution. Multi-dimensional analysis of nursing data from each plan was conducted to extract physiological indicators and potential risks associated with the practical application of candidate home care plans. Based on physiological indicators and potential risks, the evaluation effect of each scheme in practical application is simulated and analyzed using simulation data analysis method, generating a structured evaluation result set.

8. The home care method for chronic diseases using traditional Chinese medicine based on a cloud platform as described in claim 7, characterized in that, Based on the structured evaluation result set, the adaptability of each plan is adjusted through a genetic algorithm to ensure that the plan matches individual needs, thus obtaining a set of nursing plans. The specific steps are as follows: Based on the structured evaluation results set, the adaptability of each nursing plan is classified to obtain the nursing needs characteristics of different patient groups; Adaptability analysis and evaluation were conducted on nursing needs characteristics across different dimensions to obtain the degree of matching between each plan and patient needs, and to assess the adaptability of each plan to patient needs. Based on the adaptability of each plan to the patient's needs, a genetic algorithm is used to optimize the suitability of each nursing plan, resulting in a set of suitable nursing plans.

9. The cloud-based home care method for chronic diseases using traditional Chinese medicine as described in claim 8, characterized in that, The physiological indicators and symptom data refer to the patient's health data such as blood pressure, blood sugar, and heart rate transmitted back through the home terminal, as well as the patient's subjective reports of symptom changes and physical reactions.

10. The cloud-based home care method for chronic diseases using traditional Chinese medicine as described in claim 9, characterized in that, Based on the set of nursing plans, combined with physiological indicators and symptom data analysis and correction, a traditional Chinese medicine home care management plan for chronic diseases is formed. The specific steps are as follows: Based on physiological indicators and symptom data, information analysis and evaluation of patients' health status and nursing effects are conducted to identify nursing procedures that need to be optimized. Genetic algorithms are used to dynamically correct nursing procedures that need to be optimized, adjusting the intensity, frequency, and method of treatment to obtain a nursing care plan that meets the patient's needs. Based on the patient's nursing needs, the nursing plan and the feedback data are continuously adjusted and corrected to form a home care management plan for chronic diseases using traditional Chinese medicine.

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