Disease monitoring and diagnosing system for allergic rhinitis and asthma syndrome treated by traditional Chinese medicine

Abstract

The invention belongs to the technical field of intelligent medical treatment, and discloses a disease monitoring and diagnosis system for allergic rhinitis and asthma syndromes treated by traditional Chinese medicines. Comprising the steps of collecting a health portrait of a patient and traditional Chinese medicine diagnosis information and performing comprehensive differentiation to obtain a traditional Chinese medicine differentiation result; analyzing the health portrait of the patient, identifying abnormal medical indexes, performing disease diagnosis based on the abnormal medical indexes, and evaluating corresponding comprehensive clinical characterization to form a western medicine diagnosis result; performing cross validation on the traditional Chinese medicine differentiation result and the western medicine diagnosis result to obtain a comprehensive diagnosis result, and dynamically generating a personalized traditional Chinese medicine prescription in combination with the obtained patient personalized factors; environment perception factors are dynamically obtained, and the personalized traditional Chinese medicine prescription is intelligently optimized; the system provides full-process intelligent support for traditional Chinese medicine diagnosis and treatment of the allergic rhinitis and asthma syndrome, so that the diagnosis and treatment quality and the treatment effect are effectively improved, and a more scientific and effective traditional Chinese medicine treatment scheme is provided for patients.

Description

Technical Field

[0001] The present invention relates to the field of smart medical technology, and more specifically, to a disease monitoring and diagnosis system for allergic rhinitis and asthma syndrome treated with traditional Chinese medicine. Background Art

[0002] Allergic rhinitis and asthma syndrome is a common chronic inflammatory disease of the respiratory system in clinical practice. It is characterized by the joint participation of the nasal cavity and bronchi in the immune response. Patients often show symptoms such as nasal itching, sneezing, coughing, and wheezing, and the attacks have obvious seasonality and environmental sensitivity. Because allergic rhinitis and asthma syndrome have both upper and lower respiratory tract inflammation manifestations, the condition is complex and changeable, which brings challenges to diagnosis and treatment.

[0003] Modern medicine has made significant progress in the diagnosis and treatment of allergic rhinitis and asthma syndrome, but long-term use of Western medicines such as antihistamines, corticosteroids and bronchodilators is often accompanied by adverse reactions and drug resistance problems; patients are increasingly concerned about long-term dependence on drugs and the demand for more natural and holistic treatments.

[0004] Traditional Chinese medicine (TCM) plays an important role in the prevention and treatment of allergic rhinitis and asthma syndrome, showing unique advantages in regulating physical constitution, alleviating symptoms, and reducing recurrences. However, current TCM treatment plans mostly rely on experience and lack data-based standardization and personalized support. At the same time, the differences in the diagnostic systems of TCM and Western medicine, namely the lack of a unified connection between TCM's "differential diagnosis and treatment" and Western medicine's "pathological indicator diagnosis," limit the integrated application and collaborative decision-making capabilities of the two medical systems.

[0005] In view of this, the present invention proposes a disease condition monitoring and diagnosis system for allergic rhinitis and asthma syndrome treated with traditional Chinese medicine to solve the above problems. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: a disease monitoring and diagnosis system for allergic rhinitis and asthma syndrome treated with traditional Chinese medicine, comprising: Data collection module, used to integrate patient information collected from multiple channels to form a patient health portrait; The TCM syndrome differentiation module is used to obtain TCM diagnosis information, apply the TCM theoretical framework to comprehensively analyze the patient's health profile and TCM diagnosis information, identify the patient's syndrome characteristics, and use them as the TCM syndrome differentiation results; TCM diagnosis information includes pulse diagnosis information and tongue diagnosis information; Methods for identifying a patient's syndrome characteristics include: Construct a TCM syndrome resonance model, input the patient's health profile and TCM diagnosis information into the TCM syndrome resonance model, and obtain the confidence level of each TCM syndrome; compare each confidence level with a preset confidence threshold, and use the TCM syndrome with a confidence level greater than the confidence threshold as the syndrome feature; The methods for constructing a TCM syndrome resonance model include: Collect historical data from different patients, cluster and discretize the historical data, and obtain a feature set for each TCM syndrome type, which includes feature information of different TCM syndrome types; calculate the conditional probability of each feature information in the corresponding TCM syndrome type and the mutual information between each feature information and the corresponding TCM syndrome type; take the product of the conditional probability and mutual information of the same corresponding feature information as the unit resonance intensity of the corresponding feature information; take the sum of the same unit resonance intensity of the corresponding TCM syndrome type as the resonance intensity of the corresponding TCM syndrome type; obtain a variable set based on the patient health profile and TCM diagnosis information input into the TCM syndrome type resonance model; calculate the matching degree between the variable set and each feature set; and calculate the confidence level that the variable set belongs to each TCM syndrome type based on the matching degree and the resonance intensity; The Western medicine diagnosis module is used to analyze the patient's health profile through objective medical indicators, identify abnormal medical indicators, diagnose the patient's disease based on the abnormal medical indicators, and evaluate the corresponding comprehensive clinical manifestations. The Western medicine diagnosis result is formed based on the disease diagnosis results and the corresponding comprehensive clinical manifestations; Comprehensive diagnosis module, used to cross-validate the results of TCM syndrome differentiation and Western medicine diagnosis to obtain comprehensive diagnosis results; The prescription generation module is used to obtain individual patient factors and dynamically generate personalized traditional Chinese medicine prescriptions based on comprehensive diagnostic results. The prescription optimization module is used to dynamically obtain environmental perception factors and intelligently optimize personalized Chinese medicine prescriptions based on environmental perception factors.

[0007] Furthermore, patient information includes physiological indicators, symptom records, and clinical data; physiological indicators include respiratory flow, sneezing frequency, and cough intensity; symptom records include nasal symptoms and airway symptoms; clinical data include IgE levels, vital capacity, and peak expiratory flow rate; The historical data includes patient health portraits and traditional Chinese medicine diagnosis information obtained at historical moments; the patient health portraits and pulse diagnosis information in all historical data are used as historical analysis data, and the data of the same data type in the historical analysis data are used as a group of data sets; clustering processing is performed on each group of data sets to obtain multiple first clusters corresponding to each group of data sets, and a corresponding discrete label is set for each first cluster; The historical analysis data in each group of historical data are converted into corresponding discrete labels; all historical data are clustered to obtain multiple second clusters, and a corresponding TCM syndrome type is set for each second cluster; the discrete labels and tongue diagnosis information are collectively referred to as discrete information, and the number of each discrete information in each second cluster is counted and marked as information quantity; each information quantity is compared with a preset quantity threshold, and the discrete information with an information quantity greater than the quantity threshold is marked as feature information; based on the feature information of each second cluster, a feature set of each TCM syndrome type is constructed.

[0008] Furthermore, the method for identifying abnormal medical indicators includes: The patient health profile formed in real time is marked as real-time data, and the patient health profile and real-time data in the historical data are used as the patient data set; the data of the same type in the patient data set are used as a set of indicator sets, and the data in each indicator set are sorted in ascending order to generate an indicator sequence; the empirical distribution value of each data in the real-time data in the corresponding indicator sequence is calculated in sequence, and each empirical distribution value is compared with the corresponding preset distribution threshold; The distribution threshold includes a low-end threshold and a high-end threshold; If the empirical distribution value is greater than the corresponding high-end threshold, or less than the corresponding low-end threshold, the corresponding data will be regarded as an abnormal medical indicator.

[0009] Furthermore, the method for diagnosing a patient's disease based on abnormal medical indicators includes: Each indicator in the abnormal medical index is converted into the membership degree of each corresponding discrete label through fuzzification technology; a fuzzy causal network is defined, which includes nodes and connecting edges. The nodes represent abnormal medical indicators or disease names, and the connecting edges represent the fuzzy rules between two nodes. Each abnormal medical indicator after fuzzification is used as input and associated with the corresponding node in the fuzzy causal network. The nodes are matched according to the fuzzy rules in the fuzzy causal network, and fuzzy reasoning is performed using a fuzzy reasoning method to obtain fuzzy reasoning results. The fuzzy reasoning results include the membership degrees corresponding to different disease names. The disease names with membership degrees greater than a preset membership threshold are regarded as disease diagnosis results. Methods for evaluating the comprehensive clinical picture include: Different numerical labels are set for different disease names and marked as disease labels; the disease labels and abnormal medical indicators corresponding to the disease diagnosis results are input into the trained comprehensive evaluation model to obtain comprehensive clinical representations, which include disease severity, airway reactivity and inflammatory status.

[0010] Furthermore, the method for obtaining the comprehensive diagnosis result includes: A Chinese-Western mapping table is preset, which includes the correlation between each Chinese medicine syndrome type and each disease name; according to the Chinese-Western mapping table, the correlation between each Chinese medicine syndrome type in the Chinese medicine syndrome differentiation result and each disease name in the Western medicine diagnosis result is obtained in sequence, and the maximum correlation between each Chinese medicine syndrome type and the disease name is selected respectively; All maximum correlations are averaged to obtain the average correlation; the average correlation is compared with the preset correlation threshold; if the average correlation is greater than the correlation threshold, the cross-validation is successful, and the TCM syndrome differentiation results and Western medicine diagnosis results are combined to form a comprehensive diagnostic result.

[0011] Furthermore, the method for dynamically generating personalized Chinese medicine prescriptions includes: Construct a comprehensive Chinese medicine knowledge graph and obtain For each candidate prescription, add Group medication regimen, obtained The candidate prescription includes the dosage of each Chinese medicine in the candidate prescription and the time of taking the candidate prescription; A pharmacokinetic model is constructed based on the patient's individual factors and health profile; each candidate prescription is input into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each candidate prescription; the symptom time characteristics are obtained, and the drug-symptom time matching index corresponding to each candidate prescription is calculated in turn based on the matching results of the symptom time characteristics and each group of pharmacokinetic characteristics; the candidate prescription with the largest drug-symptom time matching index is used as the personalized Chinese medicine prescription.

[0012] Furthermore, pharmacokinetic characteristics include the onset time of drug effect and the maintenance time of effective blood drug concentration; symptom time characteristics include the onset time of symptoms and symptom cycle; Methods for calculating drug-symptom time matching indicators include: The sum of the taking time and the starting time of the drug effect in the candidate prescription is taken as the actual starting time of the drug effect, and the actual starting time of the drug effect is compared with the symptom onset time, and the time consistency is calculated based on the comparison results; the sum of the actual starting time of the drug effect and the effective blood drug concentration maintenance time is taken as the drug effect end time; based on the actual starting time of the drug effect and the drug effect end time, the drug effect maintenance period is established; the sum of the symptom onset time and the symptom cycle is taken as the symptom end time; based on the symptom onset time and the symptom end time, the symptom maintenance period is established; the drug effect maintenance period is matched with the symptom maintenance period, and the drug effect coverage rate is calculated based on the matching results; A weight set is preset, and the weight set includes weight coefficients corresponding to the time consistency and the drug efficacy coverage; based on the weight set, the time consistency and the drug efficacy coverage are weighted and summed to obtain the drug-disease time matching index.

[0013] Furthermore, the method for intelligently optimizing personalized Chinese medicine prescriptions includes: Environmental perception factors include climate seasonal factors and environmental monitoring factors; environmental monitoring factors include pollen concentration and air quality index; Combine environmental perception factors with comprehensive diagnostic results to form comprehensive environmental diagnostic information; based on comprehensive environmental diagnostic information and comprehensive Chinese medicine knowledge graph, obtain The candidate prescriptions of each dose are selected and marked as environmental adaptability prescriptions; each dose of environmental adaptability prescription is input into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each dose of environmental adaptability prescription; Based on the comprehensive environmental diagnostic information, the changing patterns of symptom time characteristics are dynamically predicted to obtain the environmental correction characteristics; based on the matching results of the environmental correction characteristics and each group of pharmacokinetic characteristics, the drug-symptom time matching index corresponding to each dose of the environmental adaptability prescription is calculated in turn; based on the environmental adaptability prescription with the largest drug-symptom time matching index, personalized Chinese medicine prescriptions are intelligently optimized.

[0014] Furthermore, methods for dynamically predicting the changing patterns of symptom temporal characteristics include: Different numerical labels are set for different TCM syndrome types, current seasons, and seasonal pathogenic factors characteristics, and marked as prediction labels; the disease names in the comprehensive environmental diagnosis information are replaced with corresponding disease labels, and the TCM syndrome types, current seasons, and seasonal pathogenic factors characteristics are replaced with corresponding prediction labels; the replaced comprehensive environmental diagnosis information is input into the trained variability prediction model to predict the temporal feature variability; based on the temporal feature variability, the symptom temporal features are dynamically adjusted to obtain the environmental correction features.

[0015] The technical effects and advantages of the allergic rhinitis and asthma syndrome condition monitoring and diagnosis system treated with traditional Chinese medicine of the present invention are as follows: By combining TCM syndrome differentiation with Western medicine diagnosis, the system integrates the diagnostic systems of both Chinese and Western medicine. By constructing a TCM syndrome resonance model and a fuzzy causal network, it achieves a comprehensive analysis of patient syndrome characteristics and disease diagnosis, improving the comprehensiveness and accuracy of diagnosis. Based on the patient's health profile and TCM diagnostic information, it dynamically generates personalized TCM prescriptions, and combines individualized patient factors for pharmacokinetic modeling. This allows for more accurate predictions of the effects of TCM in the patient's body, thereby designing personalized treatment plans that better meet the patient's actual needs. By dynamically acquiring environmental perception factors and integrating them with comprehensive diagnostic results, personalized TCM prescriptions are intelligently optimized, better adapting to the changing trends of patient symptoms in different environments and enhancing the targetedness and effectiveness of TCM treatment. Leveraging the advantages of TCM in conditioning constitution and preventing relapses, the system provides full-process intelligent support for TCM diagnosis and treatment of allergic rhinitis and asthma syndrome through innovative technologies such as the integration of TCM and Western medicine, personalized medication, and environmental sensing, effectively improving work efficiency, diagnosis and treatment quality, and treatment outcomes, reducing adverse reactions, and providing patients with more scientific and effective TCM treatment plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of a condition monitoring and diagnosis system for allergic rhinitis and asthma syndrome treated with traditional Chinese medicine according to Example 1 of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] Example 1 See also Figure 1 As shown, the allergic rhinitis and asthma syndrome monitoring and diagnosis system treated with traditional Chinese medicine in this embodiment includes a data acquisition module, a traditional Chinese medicine syndrome differentiation module, a Western medicine diagnosis module, a comprehensive diagnosis module, a prescription generation module and a prescription optimization module; each module is connected by wired and / or wireless means to realize data transmission between modules.

[0019] The data collection module is used to integrate patient information collected from multiple channels to form a patient health portrait.

[0020] Patient information includes physiological indicators, symptom records and clinical data; patient health portrait refers to a digital, personalized description of the patient's overall health status.

[0021] Physiological indicators include but are not limited to respiratory flow, sneeze frequency, and cough intensity, which are monitored in real time through smart wearable devices worn by patients (such as smart masks and smart chest straps). They are used to reflect the dynamic changes in the patient's respiratory tract and the severity of symptoms, and help to monitor acute attacks and fluctuations of allergic rhinitis and asthma in real time. Symptom records are patients' symptoms in daily life, such as nasal symptoms (such as the degree of nasal congestion and the intensity of nasal itching) and airway symptoms (such as the frequency of dyspnea and the degree of chest tightness). Patients fill in these records independently using mobile apps, mini-programs, or other smart terminals. They are used to provide continuous tracking of patients' subjective feelings and clinical manifestations, helping to assess the trend of disease changes. Clinical data include but are not limited to IgE (immunoglobulin E) levels, vital capacity, peak expiratory flow rate, etc., which are obtained through professional medical examinations such as lung function tests and allergen skin prick tests conducted by medical institutions. They are used to objectively reflect the patient's immune allergy status and lung function status, and are an important basis for judging the pathogenesis, severity of the disease and treatment efficacy of allergic rhinitis asthma syndrome.

[0022] The TCM syndrome differentiation module is used to obtain TCM diagnosis information, apply the TCM theoretical framework to comprehensively analyze the patient's health profile and TCM diagnosis information, identify the patient's syndrome characteristics, and use them as the TCM syndrome differentiation results.

[0023] TCM diagnostic information includes pulse and tongue diagnostic information. The TCM theoretical framework is the fundamental thinking system of TCM, primarily composed of interrelated theories such as the Yin-Yang theory, the theory of viscera and meridians, the theory of Qi, blood, and body fluids, and the theory of syndrome differentiation and treatment. It explains the physiological and pathological phenomena of the human body and their changing patterns from a holistic and syndrome differentiation perspective, and serves as the theoretical foundation guiding TCM clinical practice. Pulse diagnostic information includes pulse strength, pulse rhythm, and pulse waveform; it reflects the patient's Qi and blood circulation and the functional status of the internal organs. In allergic rhinitis and asthma syndrome, pulse can help determine the patient's body's deficiency or excess, cold or heat, Qi stagnation, and phlegm-dampness, thereby assisting in the identification of syndrome types such as Qi deficiency, lung cold, and phlegm-dampness blocking the lungs. Pulse diagnostic information is obtained through an intelligent pulse diagnosis instrument. Tongue diagnostic information includes tongue shape, tongue color, tongue coating color and tongue surface texture; it is used to reflect the cold, heat, dampness, heat toxins and organ function in the patient's body; for allergic rhinitis and asthma syndrome, tongue image can reveal the functional status of organs such as the lungs, spleen and kidneys, help identify different syndromes such as wind-cold, wind-heat, phlegm-dampness, and blood stasis, and guide the traditional Chinese medicine syndrome differentiation and treatment; tongue diagnostic information is obtained through an intelligent tongue diagnostic instrument.

[0024] Methods for identifying a patient's syndrome characteristics include: A TCM syndrome resonance model is constructed, and the patient's health profile and TCM diagnosis information are input into the TCM syndrome resonance model to obtain the confidence of each TCM syndrome; each confidence is compared with a preset confidence threshold, and the confidence threshold is pre-set by technical personnel in this field according to actual conditions; the TCM syndrome with a confidence greater than the confidence threshold is used as a syndrome feature, and the TCM syndrome with a confidence less than or equal to the confidence threshold is not used as a syndrome feature.

[0025] The methods for constructing a TCM syndrome resonance model include: Collect historical data of different patients, including patient health portraits and traditional Chinese medicine diagnosis information obtained at historical moments, which are obtained from a database built into an allergic rhinitis and asthma syndrome disease monitoring and diagnosis system; use the patient health portraits and pulse diagnosis information in all historical data as historical analysis data, and use data of the same data type in the historical analysis data as a group of data sets; perform clustering processing on each group of data sets to obtain multiple first clusters corresponding to each group of data sets, and set corresponding discrete labels for each first cluster; illustratively, the discrete labels corresponding to respiratory flow are large flow, medium flow, and small flow, and the discrete labels corresponding to peak expiratory flow rate are fast flow rate, medium flow rate, and slow flow rate, etc.; The historical analysis data in each group of historical data are converted into corresponding discrete labels respectively; all historical data are clustered to obtain multiple second clusters, and corresponding TCM syndrome types are set for each second cluster; wherein TCM syndrome types such as wind-cold lung binding syndrome, phlegm-dampness obstructing lung syndrome, lung qi deficiency syndrome, etc., each second cluster includes multiple groups of different historical data; discrete labels and tongue image diagnostic information are collectively referred to as discrete information, the number of each discrete information in each second cluster is counted and marked as information quantity; each information quantity is compared with a preset quantity threshold, and the quantity threshold is pre-set by those skilled in the art according to actual conditions; discrete information whose information quantity is greater than the quantity threshold is marked as feature information, and discrete information whose information quantity is less than or equal to the quantity threshold is not marked; based on the feature information of each second cluster, a feature set of each TCM syndrome type is constructed; it should be noted that this embodiment adopts the DBSCAN algorithm for clustering processing, and the DBSCAN algorithm is a prior art, and the specific process is not described in detail here; Calculate the conditional probability of each feature information in the corresponding TCM syndrome type and the mutual information between each feature information and the corresponding TCM syndrome type; take the product of the conditional probability and the mutual information of the same corresponding feature information as the unit resonance intensity of the corresponding feature information; take the sum of the unit resonance intensities of the same corresponding TCM syndrome type as the resonance intensity of the corresponding TCM syndrome type; obtain the corresponding discrete information based on the patient health portrait and TCM diagnosis information input into the TCM syndrome type resonance model, and form a variable set; calculate the matching degree between the variable set and each feature set; based on the matching degree and the resonance intensity, calculate the confidence that the variable set belongs to each TCM syndrome type; It should be noted that the calculation methods of conditional probability and mutual information are both existing technologies, and the specific calculation process will not be described in detail here.

[0026] The matching degree is calculated as follows: the variable set is compared with the feature set to determine the occurrence coefficient of each discrete information in the variable set; the occurrence coefficient of each discrete information in the variable set is multiplied by the corresponding unit resonance intensity in sequence to obtain the matching degree; the occurrence coefficient is determined as follows: if the discrete information in the variable set exists in the feature set, the occurrence coefficient of the corresponding discrete information is determined to be 1; if the discrete information in the variable set does not exist in the feature set, the occurrence coefficient of the corresponding discrete information is determined to be 0.

[0027] The confidence is calculated as follows: the product of the matching degree and the resonance intensity of the corresponding TCM syndrome type is used as the local confidence; the sum of all local confidences is used as the total confidence; the ratio of each local confidence to the total confidence is used as the confidence of the corresponding TCM syndrome type.

[0028] The Western medicine diagnosis module is used to analyze the patient's health profile through objective medical indicators, identify abnormal medical indicators, diagnose the patient's disease based on the abnormal medical indicators, and evaluate the corresponding comprehensive clinical manifestations. The Western medicine diagnosis results are formed based on the disease diagnosis results and the corresponding comprehensive clinical manifestations.

[0029] Methods for identifying abnormal medical indicators include: The patient health profile formed in real time is marked as real-time data, and the patient health profile and real-time data in the historical data are used as the patient data set; the data of the same type in the patient data set are used as a set of indicator sets, and the data in each indicator set are sorted in ascending order to generate an indicator sequence; the empirical distribution value of each data in the real-time data in the corresponding indicator sequence is calculated in sequence, and each empirical distribution value is compared with the corresponding preset distribution threshold; The distribution threshold includes a low-end threshold and a high-end threshold. Different indicator sets correspond to different distribution thresholds and are pre-set by those skilled in the art based on actual medical experience. If the empirical distribution value is between the corresponding low-end threshold and high-end threshold, the corresponding data will not be regarded as an abnormal medical indicator; If the empirical distribution value is greater than the corresponding high-end threshold, or less than the corresponding low-end threshold, the corresponding data will be regarded as an abnormal medical indicator.

[0030] The calculation method of the empirical distribution value is: obtain the data position of the data in the corresponding indicator sequence (that is, the ranking of the data in the indicator sequence), and count the number of data in the indicator sequence; take the ratio of the data position to the number of data as the empirical distribution value.

[0031] Methods for diagnosing disease in patients based on abnormal medical indicators include: Each indicator in the abnormal medical index is converted into the membership of each corresponding discrete label through fuzzification technology. Fuzzification technology is the process of converting precise numerical values ​​into the membership corresponding to fuzzy sets. Fuzzification technologies include triangular membership function and trapezoidal membership function. Define a fuzzy causal network. The fuzzy causal network is defined based on expert knowledge or relevant literature. A fuzzy causal network consists of nodes and edges. An edge is located between two nodes. A node represents an abnormal medical indicator or disease name. An edge is located between two nodes and represents the fuzzy rule between the two nodes. For example, if the two nodes are respiratory flow and asthma, the fuzzy rule is: if the respiratory flow corresponds to a low flow rate, then the membership degree of asthma is high. Each abnormal medical indicator after fuzzification processing is used as input and associated with the corresponding node in the fuzzy causal network. Matching is performed according to the fuzzy rules in the fuzzy causal network. Fuzzy reasoning methods (such as Mamdani fuzzy reasoning model, Sugeno fuzzy reasoning model, etc.) are used to perform fuzzy reasoning to obtain fuzzy reasoning results. The fuzzy reasoning results include the membership degrees corresponding to different disease names; the disease names with membership degrees greater than the preset membership threshold are used as disease diagnosis results; disease names such as allergic rhinitis, asthma, chronic sinusitis, etc., and the membership threshold is pre-set by technical personnel in this field according to actual conditions.

[0032] Methods for evaluating the comprehensive clinical picture include: Different numerical labels are assigned to different disease names and marked as disease labels. The disease labels corresponding to the disease diagnosis results and abnormal medical indicators are input into the trained comprehensive evaluation model to obtain a comprehensive clinical representation, which includes disease severity, airway reactivity, and inflammatory status. Among them, airway reactivity indicates the sensitivity and reaction intensity of the airway to irritants (such as allergens, cold air, exercise, etc.), and the inflammatory status indicates the degree of inflammatory response in the airway or lungs. The comprehensive evaluation model is a deep neural network model, which includes an input layer, a hidden layer, and an output layer. Each hidden layer includes multiple neurons, and each neuron is connected to the neurons in the next layer. The connections contain weights that determine the importance and influence of data transmission in the neural network. An activation function is applied to each neuron between the hidden layer and the output layer. The activation function introduces nonlinearity, allowing the network to learn more complex patterns and features. The deep neural network model is an existing technology, and the specific training process will not be described in detail here.

[0033] The comprehensive diagnosis module is used to cross-validate the results of TCM syndrome differentiation and Western medicine diagnosis to obtain a comprehensive diagnosis result.

[0034] Methods for obtaining comprehensive diagnostic results include: A Chinese-Western mapping table is preset, and the Chinese-Western mapping table includes the correlation between each TCM syndrome type and each disease name; the method for constructing the Chinese-Western mapping table is as follows: technical personnel in this field collect clinical cases containing dual diagnosis information of TCM syndrome types and disease names, that is, each clinical case records the patient's TCM syndrome type and disease name; the clinical cases corresponding to the same TCM syndrome type are regarded as a group of case sets, the number of times each disease name appears in each case set is counted, and marked as the mapping number; the total number of times all disease names appear in each case set is counted, and marked as the total mapping number; the ratio of each mapping number to the corresponding mapping total number is calculated in turn to obtain the mapping frequency; each mapping frequency is taken as the correlation between the corresponding TCM syndrome type and the corresponding disease name, and the Chinese-Western mapping table is constructed based on all the correlations; wherein the TCM syndrome types and disease names in the Chinese-Western mapping table are all related to allergic rhinitis asthma syndrome; According to the Chinese-Western medicine mapping table, the correlation between each TCM syndrome type in the TCM syndrome differentiation results and each disease name in the Western medicine diagnosis results is obtained in sequence, and the maximum correlation between each TCM syndrome type and the disease name is selected (i.e., the correlation with the largest value is selected for each TCM syndrome type, and the correlation with the largest value is also selected for each disease name); All maximum correlations are averaged to obtain the average correlation; the average correlation is compared with a preset correlation threshold, which is pre-set by technical personnel in this field based on the distribution of correlations in the Chinese and Western mapping table; if the average correlation is greater than the correlation threshold, the cross-validation is successful, and the results of TCM syndrome differentiation and Western medicine diagnosis are combined to form a comprehensive diagnostic result; if the average correlation is less than or equal to the correlation threshold, the cross-validation fails, prompting medical staff to review the results of TCM syndrome differentiation and Western medicine diagnosis.

[0035] It should be noted that the reason for cross-validating the results of TCM syndrome differentiation and Western medicine diagnosis is to quantify the correspondence between the two different medical systems and evaluate the consistency and rationality of the diagnostic results, thereby improving the accuracy and reliability of the diagnosis, promoting scientific decision-making in the integration of TCM and Western medicine, and ensuring that the comprehensive diagnostic results are more comprehensive and effective.

[0036] The prescription generation module is used to obtain individual patient factors and dynamically generate personalized Chinese medicine prescriptions based on comprehensive diagnostic results.

[0037] Methods for dynamically generating personalized Chinese medicine prescriptions include: Those skilled in the art can construct a comprehensive Chinese medicine knowledge graph by integrating information from Chinese medicine prescription information sources such as the classic prescription database (i.e., a collection of classic Chinese medicine prescriptions recorded in medical books), modern Chinese medicine literature (i.e., Chinese medicine research papers, monographs, etc.), and Chinese medicine patent database (i.e., a database containing various patent information related to Chinese medicine prescriptions). The knowledge graph is an existing technology, and the specific construction process will not be elaborated on here. According to the comprehensive diagnosis results, obtain For each candidate prescription, add Group medication regimen, obtained The medication regimen includes the dosage of each Chinese medicine in the candidate prescription and the time of taking the candidate prescription. and are all integers greater than 1, ; The group medication regimens were established by those skilled in the art based on the patient's health profile; A pharmacokinetic model is constructed based on the patient's individual factors and health profile; each candidate prescription is input into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each candidate prescription; the symptom time characteristics are obtained, and the drug-symptom time matching index corresponding to each candidate prescription is calculated in turn based on the matching results of the symptom time characteristics and each group of pharmacokinetic characteristics; the candidate prescription with the largest drug-symptom time matching index is used as the personalized Chinese medicine prescription.

[0038] Among them, individualized factors for patients include constitutional characteristics and past drug reactions; constitutional characteristics include the patient's age, gender, and weight; past drug reactions include history of adverse drug reactions and drug sensitivity; history of adverse drug reactions refers to the record of adverse or harmful reactions that occurred when the patient used a certain drug in the past; drug sensitivity refers to the intensity or sensitivity of the patient's response to the drug, which is manifested in that the same dose of the drug may produce different intensities of effect in different patients; for example, some patients are particularly sensitive to sedatives, and even small doses can produce obvious effects, while some patients may need larger doses to achieve the expected therapeutic effect; individualized factors for patients are obtained through medical history records, clinical evaluations, laboratory tests, etc. It should be noted that individual patient factors affect key parameters such as drug metabolizing enzyme activity, distribution volume and clearance rate, enabling the pharmacokinetic model to shift from the group average level to individual precise prediction; systemic characteristics such as age, gender and weight determine the basic behavior of drugs in the patient's body, while adverse drug reaction history and drug sensitivity provide key information on patient-specific reactions. After these factors are introduced as covariates into the pharmacokinetic model, they can quantify individual variations, determine the safe range of medication, and combine with the theory of traditional Chinese medicine constitution to ultimately achieve scientific, accurate and personalized traditional Chinese medicine prescription design.

[0039] A pharmacokinetic model is a mathematical model that describes the absorption, distribution, metabolism, and excretion of a drug in the body. It is used to predict the concentration-time variation pattern of a drug in the patient's body. Pharmacokinetic models include compartment models (such as single-compartment models, two-compartment models, multi-compartment models, etc.), physiological pharmacokinetic models, and population pharmacokinetic models. Pharmacokinetic models are existing technologies, and the specific construction process will not be elaborated on here.

[0040] Pharmacokinetic characteristics include the onset time of drug effect and the maintenance time of effective blood drug concentration, which together describe the time characteristics of the drug's effect in the patient's body. The onset time of drug effect refers to the time required for the drug to begin to produce therapeutic effects, and the maintenance time of effective blood drug concentration refers to the duration of time that the drug remains in the concentration range that can produce therapeutic effects in the blood. The symptom time characteristics include the symptom onset time and the symptom cycle; the symptom onset time indicates the specific time point when the patient's symptoms begin to appear, such as difficulty breathing and chest tightness when waking up at 5 am, and starting to feel nasal congestion and itchy throat when brushing teeth after getting up at 8 am; the symptom cycle refers to the entire time period from the onset to the disappearance of symptoms; for example, a single nasal congestion attack lasts about 3 to 4 hours, and a night cough lasts about 20 minutes; the symptom time characteristics are filled in by the patient independently using a mobile phone app, mini-program or other smart terminal.

[0041] Methods for calculating drug-symptom time matching indicators include: The sum of the taking time and the starting time of the drug effect in the candidate prescription is taken as the actual starting time of the drug effect, and the actual starting time of the drug effect is compared with the symptom onset time, and the time consistency is calculated based on the comparison results; the sum of the actual starting time of the drug effect and the effective blood drug concentration maintenance time is taken as the drug effect end time; based on the actual starting time of the drug effect and the drug effect end time, the drug effect maintenance period is established; the sum of the symptom onset time and the symptom cycle is taken as the symptom end time; based on the symptom onset time and the symptom end time, the symptom maintenance period is established; the drug effect maintenance period is matched with the symptom maintenance period, and the drug effect coverage rate is calculated based on the matching results; A preset weight set includes weight coefficients corresponding to time consistency and drug efficacy coverage, which are pre-set by technical personnel in this field according to actual conditions; based on the weight set, the time consistency and drug efficacy coverage are weighted and summed to obtain the drug-disease time matching index.

[0042] Methods for calculating the temporal coincidence based on the comparison results include: If the comparison result shows that the actual onset time of drug effect is earlier than or equal to the onset time of symptoms, the time consistency is If the comparison result shows that the actual onset time of drug effect is later than the onset time of symptoms, the time consistency is calculated as follows: the difference between the actual onset time of drug effect and the onset time of symptoms is used as the time difference; the ratio of the time difference to the preset maximum acceptable delay is used as the response delay rate; the difference between the time difference and the response delay rate is used as the time consistency; It should be noted that the value range of time coincidence is , so when the response delay rate is greater than 1, the time consistency is 0.

[0043] Methods for calculating efficacy coverage based on matching results include: The ratio of the matching result to the time of symptom onset is taken as the drug efficacy coverage; the matching result is the length of the overlapping period between the drug efficacy maintenance period and the symptom maintenance period.

[0044] The prescription optimization module is used to dynamically obtain environmental perception factors and intelligently optimize personalized Chinese medicine prescriptions based on environmental perception factors.

[0045] Environmental perception factors include climate seasonal factors and environmental monitoring factors; Climate and seasonal factors include the current season and the characteristics of seasonal pathogens; The current season is the current season. Each season has its own unique climatic characteristics and impact on the human body. Traditional Chinese Medicine believes that human physiological functions adjust with the seasons, such as spring for growth, summer for growth, autumn for contraction, and winter for dormancy. The current season is automatically determined based on the current date and is usually divided by month or solar term. Seasonal pathogenic factors characteristics refer to exogenous pathogenic factors with specific pathogenic properties that arise or prevail with seasonal changes; among them, wind pathogens are dominant in spring, which easily cause wind-cold and wind-heat diseases; heat pathogens are dominant in summer, which easily cause heat-heat and damp-heat diseases; dryness pathogens are dominant in autumn, which easily cause dryness and damage to body fluids; and cold pathogens are dominant in winter, which easily cause cold stagnation and obstruction diseases; seasonal pathogenic factors characteristics are obtained from the TCM theoretical knowledge base pre-established by technical personnel in this field according to the current season, and the TCM theoretical knowledge base includes exogenous pathogenic factors that dominate in different seasons.

[0046] Environmental monitoring factors include pollen concentration and air quality index; Pollen concentration refers to the level of various plant pollen in the air, such as tree pollen (such as pine and birch) and herbaceous pollen (such as grass and weeds). High pollen concentration can trigger allergic reactions, such as allergic rhinitis and asthma, necessitating the inclusion of anti-allergic and anti-wind-dispelling medicinal ingredients in personalized traditional Chinese medicine prescriptions. Pollen concentration is obtained by accessing the pollen monitoring network API provided by meteorological agencies, disease control centers, or third-party pollen monitoring platforms, and can be returned by region and time. The air quality index refers to a comprehensive indicator that measures the degree of air pollution. When the air quality is poor, it is necessary to add medicinal ingredients that clear the lungs, detoxify, and protect the body fluids to personalized traditional Chinese medicine prescriptions. The air quality index is obtained by accessing the air quality monitoring API publicly available from environmental protection departments or local environmental monitoring agencies.

[0047] Methods for intelligent optimization of personalized TCM prescriptions include: Combine environmental perception factors with comprehensive diagnostic results to form comprehensive environmental diagnostic information; based on comprehensive environmental diagnostic information and comprehensive Chinese medicine knowledge graph, obtain The candidate prescriptions are marked as environmentally suitable prescriptions. is an integer greater than 1; each dose of the environmental adaptability prescription is input into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each dose of the environmental adaptability prescription; Based on the comprehensive environmental diagnostic information, the changing patterns of symptom time characteristics are dynamically predicted to obtain environmental correction characteristics (i.e., symptom time characteristics under the influence of environmental perception factors); based on the matching results of the environmental correction characteristics and each group of pharmacokinetic characteristics, the drug-symptom time matching index corresponding to each dose of the environmental adaptability prescription is calculated in turn; based on the environmental adaptability prescription with the largest drug-symptom time matching index, personalized Chinese medicine prescriptions are intelligently optimized.

[0048] Methods for dynamically predicting the changing patterns of symptom temporal characteristics include: Different numerical labels are set for different TCM syndrome types, current seasons, and seasonal pathogenic characteristics, and marked as prediction labels. The disease names in the comprehensive environmental diagnosis information are replaced with corresponding disease labels, and the TCM syndrome types, current seasons, and seasonal pathogenic characteristics are all replaced with corresponding prediction labels. The replaced comprehensive environmental diagnosis information is input into the trained variability prediction model to predict the temporal feature variability. The variability prediction model is a deep neural network model. Based on the temporal feature variability, the symptom temporal features are dynamically adjusted to obtain the environmental correction features. Among them, the temporal feature variability is an indicator used to measure the degree of deviation of the patient's symptom temporal features caused by environmental perception factors; the temporal feature variability includes the variability corresponding to the symptom onset time and the symptom cycle; the method for dynamically adjusting the symptom temporal features based on the temporal feature variability is: the product of each feature in the symptom temporal feature and the corresponding variability in the temporal feature variability is used as the variation of each feature in the symptom temporal feature; the sum of each feature in the symptom temporal feature and the corresponding variation is used as the environmental correction feature.

[0049] For example, the patient's symptom onset time in the symptom time feature is 8 o'clock in the morning, and the predicted time feature variation is , so the variation in symptom onset time is , the symptom onset time in the environmental correction feature is 6:00 in the morning.

[0050] This embodiment adopts a method that combines TCM syndrome differentiation with Western medicine diagnosis, integrating the diagnostic systems of both Chinese and Western medicine. By constructing a TCM syndrome resonance model and a fuzzy causal network, it achieves a comprehensive analysis of patient syndrome characteristics and disease diagnosis, thereby improving the comprehensiveness and accuracy of diagnosis. Based on the patient's health profile and TCM diagnostic information, personalized TCM prescriptions are dynamically generated, and pharmacokinetic modeling is performed in combination with the patient's individual factors. This can more accurately predict the characteristics of the TCM's effects in the patient's body, thereby designing a personalized treatment plan that better meets the patient's actual needs. By dynamically acquiring environmental perception factors and integrating them with comprehensive diagnostic results, personalized TCM prescriptions are intelligently optimized, which can better adapt to the changing trends of patient symptoms in different environments and improve the targetedness and effectiveness of TCM treatment. It fully leverages the advantages of TCM in regulating physical constitution and preventing recurrence. Through innovative technical means such as the integration of TCM and Western medicine, personalized medication, and environmental perception, it provides full-process intelligent support for TCM diagnosis and treatment of allergic rhinitis and asthma syndrome, thereby effectively improving work efficiency, diagnosis and treatment quality, and treatment effects, reducing adverse reactions, and providing patients with more scientific and effective TCM treatment plans.

[0051] Example 2 This application also provides an electronic device. The electronic device may include one or more processors and one or more memories. The memories may store computer-readable code that, when executed by the one or more processors, may implement the aforementioned system for monitoring and diagnosing allergic rhinitis and asthma syndrome treated with traditional Chinese medicine.

[0052] The method or system according to the embodiment of the present application can also be implemented with the help of the architecture of the electronic device shown in this application. The electronic device may include a bus, one or more CPUs, ROM, RAM, a communication port connected to a network, input / output, a hard disk, etc. The storage device in the electronic device, such as a ROM or a hard disk, can store the allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for treatment with traditional Chinese medicine provided in this application. Furthermore, the electronic device may also include a user interface. Of course, the architecture shown in this application is only exemplary. When implementing different devices, one or more components in the electronic device shown in this application can be omitted according to actual needs.

[0053] Example 3 One embodiment of the present application discloses a computer-readable storage medium. Computer-readable instructions are stored on the computer-readable storage medium. When the computer-readable instructions are executed by a processor, the allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to the embodiment of the present application described with reference to the above figures can be executed. The storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0054] In addition, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the present application provides a non-transitory machine-readable storage medium storing machine-readable instructions that can be executed by a processor to execute instructions corresponding to the method steps provided in the present application, such as a monitoring and diagnosis system for allergic rhinitis and asthma syndrome treated with traditional Chinese medicine. When the computer program is executed by a central processing unit (CPU), the above-mentioned functions defined in the method of the present application are performed.

[0055] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will be able to modify the technical solutions described in the foregoing embodiments or to substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

[0056] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0057] In the description of the present invention, it should be understood that the terms "first", "second", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0058] In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0059] In the description of the present invention, “several” means one or more, and “a large number” means two or more.

[0060] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0061] The formulas in this manual are all dimensionless and calculated using numerical values. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field based on actual conditions.

[0062] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

Claims

1. A system for monitoring and diagnosing allergic rhinitis and asthma syndrome treated with traditional Chinese medicine, characterized in that: include: Data collection module, used to integrate patient information collected from multiple channels to form a patient health portrait; The TCM syndrome differentiation module is used to obtain TCM diagnosis information, apply the TCM theoretical framework to comprehensively analyze the patient's health profile and TCM diagnosis information, identify the patient's syndrome characteristics, and use them as the TCM syndrome differentiation results; TCM diagnosis information includes pulse diagnosis information and tongue diagnosis information; Methods for identifying a patient's syndrome characteristics include: Construct a TCM syndrome resonance model, input the patient's health profile and TCM diagnosis information into the TCM syndrome resonance model, and obtain the confidence level of each TCM syndrome; compare each confidence level with a preset confidence threshold, and use the TCM syndrome with a confidence level greater than the confidence threshold as the syndrome feature; The methods for constructing TCM syndrome resonance models include: Collect historical data from different patients, cluster and discretize the historical data, and obtain a feature set for each TCM syndrome type, which includes feature information of different TCM syndrome types; calculate the conditional probability of each feature information in the corresponding TCM syndrome type and the mutual information between each feature information and the corresponding TCM syndrome type; take the product of the conditional probability and mutual information of the same corresponding feature information as the unit resonance intensity of the corresponding feature information; take the sum of the same unit resonance intensity of the corresponding TCM syndrome type as the resonance intensity of the corresponding TCM syndrome type; obtain a variable set based on the patient health profile and TCM diagnosis information input into the TCM syndrome type resonance model; calculate the matching degree between the variable set and each feature set; and calculate the confidence level that the variable set belongs to each TCM syndrome type based on the matching degree and the resonance intensity; The Western medicine diagnosis module is used to analyze the patient's health profile through objective medical indicators, identify abnormal medical indicators, diagnose the patient's disease based on the abnormal medical indicators, and evaluate the corresponding comprehensive clinical manifestations. The Western medicine diagnosis result is formed based on the disease diagnosis results and the corresponding comprehensive clinical manifestations; Comprehensive diagnosis module, used to cross-validate the results of TCM syndrome differentiation and Western medicine diagnosis to obtain comprehensive diagnosis results; The prescription generation module is used to obtain individual patient factors and dynamically generate personalized traditional Chinese medicine prescriptions based on comprehensive diagnostic results. The prescription optimization module is used to dynamically obtain environmental perception factors and intelligently optimize personalized Chinese medicine prescriptions based on environmental perception factors.

2. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 1, characterized in that: Patient information includes physiological indicators, symptom records, and clinical data; physiological indicators include respiratory flow, sneezing frequency, and cough intensity; symptom records include nasal symptoms and airway symptoms; clinical data include IgE levels, vital capacity, and peak expiratory flow rate; The historical data includes patient health portraits and traditional Chinese medicine diagnosis information obtained at historical moments; the patient health portraits and pulse diagnosis information in all historical data are used as historical analysis data, and the data of the same data type in the historical analysis data are used as a group of data sets; clustering processing is performed on each group of data sets to obtain multiple first clusters corresponding to each group of data sets, and a corresponding discrete label is set for each first cluster; The historical analysis data in each group of historical data are converted into corresponding discrete labels; all historical data are clustered to obtain multiple second clusters, and a corresponding TCM syndrome type is set for each second cluster; the discrete labels and tongue diagnosis information are collectively referred to as discrete information, and the number of each discrete information in each second cluster is counted and marked as information quantity; each information quantity is compared with a preset quantity threshold, and the discrete information with an information quantity greater than the quantity threshold is marked as feature information; based on the feature information of each second cluster, a feature set of each TCM syndrome type is constructed.

3. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 2, characterized in that: Methods for identifying abnormal medical indicators include: The patient health profile formed in real time is marked as real-time data, and the patient health profile and real-time data in the historical data are used as the patient data set; the data of the same type in the patient data set are used as a set of indicator sets, and the data in each indicator set are sorted in ascending order to generate an indicator sequence; the empirical distribution value of each data in the real-time data in the corresponding indicator sequence is calculated in sequence, and each empirical distribution value is compared with the corresponding preset distribution threshold; The distribution threshold includes a low-end threshold and a high-end threshold; If the empirical distribution value is greater than the corresponding high-end threshold, or less than the corresponding low-end threshold, the corresponding data will be regarded as an abnormal medical indicator.

4. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 3, characterized in that: Methods for diagnosing disease in patients based on abnormal medical indicators include: Each indicator in the abnormal medical index is converted into the membership degree of each corresponding discrete label through fuzzification technology; a fuzzy causal network is defined, which includes nodes and connecting edges. The nodes represent abnormal medical indicators or disease names, and the connecting edges represent the fuzzy rules between two nodes. Each abnormal medical indicator after fuzzification is used as input and associated with the corresponding node in the fuzzy causal network. The nodes are matched according to the fuzzy rules in the fuzzy causal network, and fuzzy reasoning is performed using a fuzzy reasoning method to obtain fuzzy reasoning results. The fuzzy reasoning results include the membership degrees corresponding to different disease names. The disease names with membership degrees greater than a preset membership threshold are regarded as disease diagnosis results. Methods for evaluating the comprehensive clinical picture include: Different numerical labels are set for different disease names and marked as disease labels; the disease labels and abnormal medical indicators corresponding to the disease diagnosis results are input into the trained comprehensive evaluation model to obtain comprehensive clinical representations, which include disease severity, airway reactivity and inflammatory status.

5. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 4, characterized in that: Methods for obtaining comprehensive diagnostic results include: A Chinese-Western mapping table is preset, which includes the correlation between each Chinese medicine syndrome type and each disease name; according to the Chinese-Western mapping table, the correlation between each Chinese medicine syndrome type in the Chinese medicine syndrome differentiation result and each disease name in the Western medicine diagnosis result is obtained in sequence, and the maximum correlation between each Chinese medicine syndrome type and the disease name is selected respectively; All maximum correlations are averaged to obtain the average correlation; the average correlation is compared with the preset correlation threshold; if the average correlation is greater than the correlation threshold, the cross-validation is successful, and the TCM syndrome differentiation results and Western medicine diagnosis results are combined to form a comprehensive diagnostic result.

6. The allergic rhinitis and asthma syndrome monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 5, characterized in that: Methods for dynamically generating personalized Chinese medicine prescriptions include: Construct a comprehensive Chinese medicine knowledge graph and obtain For each candidate prescription, add Group medication regimen, obtained The candidate prescription includes the dosage of each Chinese medicine in the candidate prescription and the time of taking the candidate prescription; A pharmacokinetic model is constructed based on the patient's individual factors and health profile; each candidate prescription is input into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each candidate prescription; the symptom time characteristics are obtained, and the drug-symptom time matching index corresponding to each candidate prescription is calculated in turn based on the matching results of the symptom time characteristics and each group of pharmacokinetic characteristics; the candidate prescription with the largest drug-symptom time matching index is used as the personalized Chinese medicine prescription.

7. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 6, characterized in that: Pharmacokinetic characteristics include the onset time of drug effect and the duration of maintenance of effective blood drug concentration; Symptom temporal characteristics include symptom onset time and symptom cycle; Methods for calculating drug-symptom time matching indicators include: The sum of the taking time and the starting time of the drug effect in the candidate prescription is taken as the actual starting time of the drug effect, and the actual starting time of the drug effect is compared with the symptom onset time, and the time consistency is calculated based on the comparison results; the sum of the actual starting time of the drug effect and the effective blood drug concentration maintenance time is taken as the drug effect end time; based on the actual starting time of the drug effect and the drug effect end time, the drug effect maintenance period is established; the sum of the symptom onset time and the symptom cycle is taken as the symptom end time; based on the symptom onset time and the symptom end time, the symptom maintenance period is established; the drug effect maintenance period is matched with the symptom maintenance period, and the drug effect coverage rate is calculated based on the matching results; A weight set is preset, and the weight set includes weight coefficients corresponding to the time consistency and the drug efficacy coverage; based on the weight set, the time consistency and the drug efficacy coverage are weighted and summed to obtain the drug-disease time matching index.

8. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 7, characterized in that: Methods for intelligent optimization of personalized TCM prescriptions include: Environmental perception factors include climate seasonal factors and environmental monitoring factors; environmental monitoring factors include pollen concentration and air quality index; Combine environmental perception factors with comprehensive diagnostic results to form comprehensive environmental diagnostic information; based on comprehensive environmental diagnostic information and comprehensive Chinese medicine knowledge graph, obtain The candidate prescriptions of each dose are selected and marked as environmental adaptability prescriptions; each dose of environmental adaptability prescription is input into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each dose of environmental adaptability prescription; Based on the comprehensive environmental diagnostic information, the changing patterns of symptom time characteristics are dynamically predicted to obtain the environmental correction characteristics; based on the matching results of the environmental correction characteristics and each group of pharmacokinetic characteristics, the drug-symptom time matching index corresponding to each dose of the environmental adaptability prescription is calculated in turn; based on the environmental adaptability prescription with the largest drug-symptom time matching index, personalized Chinese medicine prescriptions are intelligently optimized.

9. The allergic rhinitis and asthma syndrome monitoring and diagnosis system treated with traditional Chinese medicine according to claim 8, characterized in that: Methods for dynamically predicting the changing patterns of symptom temporal characteristics include: Different numerical labels are set for different TCM syndrome types, current seasons, and seasonal pathogenic factors characteristics, and marked as prediction labels; the disease names in the comprehensive environmental diagnosis information are replaced with corresponding disease labels, and the TCM syndrome types, current seasons, and seasonal pathogenic factors characteristics are replaced with corresponding prediction labels; the replaced comprehensive environmental diagnosis information is input into the trained variability prediction model to predict the temporal feature variability; based on the temporal feature variability, the symptom temporal features are dynamically adjusted to obtain the environmental correction features.

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