Traditional Chinese medicine treatment of allergic rhinitis asthma syndrome condition monitoring and diagnostic system

Abstract

The application belongs to the technical field of intelligent medical treatment, and discloses a disease condition monitoring and diagnosis system for allergic rhinitis asthma syndrome treated by traditional Chinese medicine; the system comprises the following steps: collecting patient health portraits and traditional Chinese medicine diagnosis information and comprehensively analyzing and distinguishing the information to obtain a traditional Chinese medicine syndrome differentiation result; analyzing the patient health portraits, identifying abnormal medical indexes, performing disease diagnosis based on the abnormal medical indexes, and evaluating corresponding comprehensive clinical manifestations to form a western medicine diagnosis result; cross- verifying the traditional Chinese medicine syndrome 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 acquired patient individual factors; dynamically acquiring environmental perception factors and intelligently optimizing the personalized traditional Chinese medicine prescription; the application provides full-process intelligent support for traditional Chinese medicine diagnosis and treatment of allergic rhinitis asthma syndrome, thereby effectively improving diagnosis and treatment quality and treatment effect, and providing a more scientific and effective traditional Chinese medicine treatment scheme for patients.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent medical technology, more specifically, the present application relates to the allergic rhinitis asthma syndrome disease monitoring and diagnosis system of traditional Chinese medicine treatment. BACKGROUND

[0002] Allergic rhinitis asthma syndrome is a common chronic inflammatory disease of the respiratory system, characterized by nasal and bronchial joint immune response, patients often show nasal itching, sneezing, coughing, wheezing and other symptoms, and the onset has obvious seasonality and environmental sensitivity; Because allergic rhinitis asthma syndrome has upper and lower respiratory tract inflammation, the disease is complex and variable, which brings challenges to diagnosis and treatment.

[0003] Modern medicine has made significant progress in the diagnosis and treatment of allergic rhinitis asthma syndrome, but long-term use of antihistamines, glucocorticoids and bronchodilators and other western medicines often accompanied by adverse reactions and drug resistance problems; Patients are worried about long-term dependence on drugs and the growing demand for more natural and holistic treatment methods.

[0004] Traditional Chinese medicine has important value in the prevention and treatment of allergic rhinitis asthma syndrome, especially in regulating constitution, relieving symptoms and reducing recurrence, and it shows unique advantages; However, the current treatment plan of traditional Chinese medicine depends on experience, and lacks standardized and personalized support based on data; At the same time, the difference between traditional Chinese medicine and western medicine in the diagnosis system, that is, the lack of unified correlation between traditional Chinese medicine "treatment based on syndrome differentiation" and western medicine "pathological index diagnosis", limits the fusion application and collaborative decision-making ability of the two medical systems.

[0005] In view of this, the present application proposes the allergic rhinitis asthma syndrome disease monitoring and diagnosis system of traditional Chinese medicine treatment to solve the above problems. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purpose, the present application provides the following technical scheme: the allergic rhinitis asthma syndrome disease monitoring and diagnosis system of traditional Chinese medicine treatment, comprising:

[0007] The data acquisition module is used for integrating the patient information collected by multiple channels to form a patient health portrait;

[0008] The TCM syndrome differentiation module is used for obtaining TCM diagnosis information, applying TCM theoretical framework to comprehensively analyze the patient health portrait and TCM diagnosis information, identifying the patient's syndrome characteristics, and serving as the TCM syndrome differentiation result; The TCM diagnosis information includes pulse diagnosis information and tongue diagnosis information;

[0009] The method for identifying the patient's syndrome characteristics comprises:

[0010] The TCM syndrome resonance model is constructed, the patient health portrait and the TCM diagnosis information are input into the TCM syndrome resonance model, and the confidence of each TCM syndrome is obtained; each confidence is compared with a preset confidence threshold, and the TCM syndrome with a confidence greater than the confidence threshold is taken as a syndrome feature;

[0011] The method for constructing the TCM syndrome resonance model comprises the following steps:

[0012] The historical data of different patients are collected, the historical data are clustered and discretized, the feature set of each TCM syndrome is obtained, the feature set comprises the feature information of different TCM syndromes, the conditional probability of each feature information in the corresponding TCM syndrome and the mutual information between each feature information and the corresponding TCM syndrome are calculated, the product of the conditional probability and the mutual information of the corresponding feature information is taken as the unit resonance strength of the corresponding feature information, the sum of the unit resonance strengths of the corresponding TCM syndromes is taken as the resonance strength of the corresponding TCM syndrome, the variable set is obtained according to the patient health portrait and the TCM diagnosis information input into the TCM syndrome resonance model, the matching degree between the variable set and each feature set is calculated, and the confidence of the variable set belonging to each TCM syndrome is calculated based on the matching degree and the resonance strength;

[0013] The western medicine diagnosis module is used for objective medical index analysis on the patient health portrait, identification of abnormal medical indexes, disease diagnosis of the patient based on the abnormal medical indexes, and evaluation of the corresponding comprehensive clinical manifestations, and the western medicine diagnosis result is constituted according to the disease diagnosis result and the corresponding comprehensive clinical manifestations;

[0014] The comprehensive diagnosis module is used for cross verification of the TCM syndrome differentiation result and the western medicine diagnosis result, and the comprehensive diagnosis result is obtained;

[0015] The prescription generation module is used for obtaining the individualized factors of the patient, and dynamically generating the individualized traditional Chinese medicine prescription in combination with the comprehensive diagnosis result;

[0016] The prescription optimization module is used for dynamically obtaining the environmental perception factors, and intelligently optimizing the individualized traditional Chinese medicine prescription based on the environmental perception factors.

[0017] Further, the patient information comprises physiological indexes, symptom records and clinical data; the physiological indexes comprise respiratory flow, sneezing frequency and cough intensity, the symptom records comprise nasal symptoms and airway symptoms, and the clinical data comprises IgE level, vital capacity and peak expiratory flow rate;

[0018] The historical data include patient health portraits and TCM diagnosis information acquired at historical time points; the patient health portraits and pulse diagnosis information in all historical data are taken as historical analysis data, and data of the same type in the historical analysis data are taken as a set of data collection; each set of data collection is respectively subjected to clustering processing to obtain a plurality of first clusters corresponding to each set of data collection, and a corresponding discrete label is respectively set for each first cluster;

[0019] The historical analysis data in each set of historical data are respectively converted into corresponding discrete labels; all historical data are subjected to clustering processing to obtain a plurality of second clusters, and a corresponding TCM syndrome type is respectively set for each second cluster; the discrete labels and tongue diagnosis information are collectively referred to as discrete information, the number of each discrete information in each second cluster is counted and marked as an information number; each information number is compared with a preset number threshold value, and the discrete information with an information number greater than the number threshold value is marked as a feature information; and a feature set of each TCM syndrome type is constituted according to the feature information of each second cluster.

[0020] Further, the method for identifying abnormal medical indicators comprises:

[0021] The patient health portrait formed in real time is marked as real-time data, and the patient health portrait in the historical data and the real-time data are taken as a patient data set; the same type of data in the patient data set is taken as a set of indicators, and the data in each set of indicators is subjected to ascending order sorting to generate an indicator sequence; the experience distribution value of each data in the real-time data in the corresponding indicator sequence is calculated in turn, and each experience distribution value is compared with a corresponding preset distribution threshold value;

[0022] The distribution threshold value includes a low-end threshold value and a high-end threshold value;

[0023] If the experience distribution value is greater than the corresponding high-end threshold value or less than the corresponding low-end threshold value, the corresponding data is taken as an abnormal medical indicator.

[0024] Further, the method for diagnosing diseases of a patient based on abnormal medical indicators comprises:

[0025] Each indicator in the abnormal medical indicators is respectively converted into the membership of each corresponding discrete label through a fuzzy technology; a fuzzy causal network is defined, the fuzzy causal network includes nodes and connection edges, the nodes represent abnormal medical indicators or disease names, and the connection edges represent fuzzy rules between two nodes;

[0026] Each abnormal medical index after the fuzzification processing is taken as an input, is associated with a corresponding node in the fuzzy causal network respectively, and is matched according to the fuzzy rules in the fuzzy causal network, a fuzzy reasoning method is used for fuzzy reasoning, and a fuzzy reasoning result is obtained, the fuzzy reasoning result includes membership degrees corresponding to different disease names; a disease name with a membership degree greater than a preset membership threshold is taken as a disease diagnosis result;

[0027] The method for evaluating the comprehensive clinical manifestations includes:

[0028] Different digital labels are set for different disease names, and are marked as disease labels; the disease labels corresponding to the disease diagnosis result and the abnormal medical indexes are input into the trained comprehensive evaluation model to obtain comprehensive clinical manifestations, and the comprehensive clinical manifestations include disease severity, airway reactivity and inflammation state.

[0029] Further, the method for obtaining the comprehensive diagnosis result includes:

[0030] A preset Chinese-Western mapping table is obtained, the Chinese-Western mapping table includes the correlation degrees between each TCM syndrome type and each disease name; according to the Chinese-Western mapping table, the correlation degrees between each TCM syndrome type in the TCM syndrome differentiation result and each disease name in the Western medical diagnosis result are obtained in turn, and the maximum correlation degrees corresponding to each TCM syndrome type and disease name are selected respectively.

[0031] All the maximum correlation degrees are processed by mean value to obtain an average correlation degree; the average correlation degree is compared with a preset correlation threshold; if the average correlation degree is greater than the correlation threshold, the cross-validation is successful, and the TCM syndrome differentiation result and the Western medical diagnosis result are combined to obtain a comprehensive diagnosis result.

[0032] Further, the method for dynamically generating a personalized traditional Chinese medicine prescription includes:

[0033] A comprehensive traditional Chinese medicine knowledge graph is constructed, and according to the comprehensive diagnosis result, a candidate medicine prescription is obtained from the comprehensive traditional Chinese medicine knowledge graph. A candidate medicine prescription is obtained from the comprehensive traditional Chinese medicine knowledge graph. A candidate medicine prescription is obtained from the comprehensive traditional Chinese medicine knowledge graph. A candidate medicine prescription is obtained from the comprehensive traditional Chinese medicine knowledge graph.

[0034] A drug kinetic model is constructed according to the patient individualization factors and the patient health portrait; each candidate medicine prescription is input into the drug kinetic model to obtain a drug kinetic characteristic corresponding to each candidate medicine prescription; a symptom time characteristic is obtained, and according to the matching result of the symptom time characteristic and each group of drug kinetic characteristics, a drug-symptom time matching index corresponding to each candidate medicine prescription is calculated in turn; the candidate medicine prescription with the maximum drug-symptom time matching index is taken as a personalized traditional Chinese medicine prescription.

[0035] Further, the pharmacokinetic characteristics include a pharmacodynamic onset time and an effective blood drug concentration maintenance time; the symptom time characteristics include a symptom onset time and a symptom period;

[0036] The method for calculating the drug-symptom time matching index comprises:

[0037] The sum of the taking time in the candidate prescription and the pharmacodynamic onset time is taken as an actual pharmacodynamic onset time, the actual pharmacodynamic onset time is compared with the symptom onset time, and a time coincidence degree is calculated according to the comparison result; the sum of the actual pharmacodynamic onset time and the effective blood drug concentration maintenance time is taken as an end time of pharmacodynamics; a pharmacodynamic maintenance period is established according to the actual pharmacodynamic onset time and the end time of pharmacodynamics; the sum of the symptom onset time and the symptom period is taken as an end time of symptoms; a symptom maintenance period is established according to the symptom onset time and the end time of symptoms; the pharmacodynamic maintenance period and the symptom maintenance period are matched, and a pharmacodynamic coverage rate is calculated according to the matching result;

[0038] A preset weight set is provided, the weight set including weight coefficients corresponding to the time coincidence degree and the pharmacodynamic coverage rate; the time coincidence degree and the pharmacodynamic coverage rate are weighted and summed based on the weight set to obtain the drug-symptom time matching index.

[0039] Further, the method for intelligently optimizing the individualized traditional Chinese medicine prescription comprises:

[0040] The environmental perception factors include climate seasonal factors and environmental monitoring factors; the environmental monitoring factors include pollen concentration and air quality index;

[0041] The environmental perception factors are combined with the comprehensive diagnosis result to form comprehensive environmental diagnosis information; the comprehensive environmental diagnosis information and the comprehensive traditional Chinese medicine knowledge graph are used to re-obtain a candidate prescription for each dose and mark it as an environment adaptive prescription; each environment adaptive prescription for each dose is input into a pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each environment adaptive prescription for each dose;

[0042] The change rule of the symptom time characteristics is dynamically predicted according to the comprehensive environmental diagnosis information to obtain an environmental correction characteristic; the drug-symptom time matching index corresponding to each environment adaptive prescription for each dose is calculated in sequence according to the matching result of the environmental correction characteristic and each group of pharmacokinetic characteristics; the individualized traditional Chinese medicine prescription is intelligently optimized according to the environment adaptive prescription with the largest drug-symptom time matching index.

[0043] Further, the method for dynamically predicting the change rule of the symptom time characteristics comprises:

[0044] Different digital labels are set for different TCM syndromes, current seasons and seasonal pathogenic factors, and are marked as prediction labels; the disease names in the comprehensive environmental diagnosis information are replaced by corresponding disease labels, and the TCM syndromes, current seasons and seasonal pathogenic factors are replaced by corresponding prediction labels; the replaced comprehensive environmental diagnosis information is input into the trained variation degree prediction model to predict the time characteristic variation degree; based on the time characteristic variation degree, the symptom time characteristics are dynamically adjusted to obtain the environmental correction characteristics.

[0045] The technical effects and advantages of the allergic rhinitis asthma syndrome disease monitoring and diagnosis system for traditional Chinese medicine treatment in the application are as follows:

[0046] By combining TCM syndrome differentiation with Western medicine diagnosis, the TCM and Western medicine diagnosis systems are integrated, the comprehensive analysis of the patient's syndrome characteristics and disease diagnosis is realized by constructing a TCM syndrome resonance model and a fuzzy causal network, and the comprehensiveness and accuracy of diagnosis are improved; based on the patient's health portrait and TCM diagnosis information, a personalized traditional Chinese medicine prescription is dynamically generated, and pharmacokinetic modeling is combined with the patient's individual factors, which can more accurately predict the action characteristics of traditional Chinese medicine in the patient's body, so as to design a more personalized treatment plan that meets the actual needs of the patient; by dynamically obtaining environmental perception factors and integrating them with the comprehensive diagnosis results, the intelligent optimization of the personalized traditional Chinese medicine prescription can better adapt to the changing trend of the patient's symptoms in different environments, and improve the targeting and effectiveness of traditional Chinese medicine treatment; the advantages of traditional Chinese medicine in regulating constitution and preventing recurrence are fully utilized, and the intelligent support for the whole process of TCM diagnosis and treatment of allergic rhinitis asthma syndrome is provided through the integration of TCM and Western medicine, personalized medication and environmental perception, so as to effectively improve the work efficiency, diagnosis and treatment quality and treatment effect, reduce adverse reactions, and provide more scientific and effective TCM treatment plan for patients. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The schematic diagram of the allergic rhinitis asthma syndrome disease monitoring and diagnosis system for traditional Chinese medicine treatment in the application is shown in Fig. 1. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the application will be described below in conjunction with the drawings in the embodiments of the application. Obviously, the described embodiments are only a part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the application.

[0049] Embodiment 1

[0050] Please refer to Figure 1As shown, the allergic rhinitis-asthma syndrome condition monitoring and diagnosis system for treating traditional Chinese medicine in the 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. The various modules are connected through wired and / or wireless means to achieve data transmission between the modules.

[0051] The data acquisition module is used to integrate patient information collected through multiple channels to form a patient health portrait.

[0052] The patient information includes physiological indicators, symptom records, and clinical data. The patient health portrait refers to a digital and personalized overall health status description constructed for the patient.

[0053] The physiological indicators include, but are not limited to, respiratory flow, sneezing frequency, cough intensity, etc., which are monitored in real time through smart wearable devices worn by the patient, such as smart masks, smart chest bands, etc. They are used to reflect the dynamic changes of the patient's respiratory tract and the severity of symptoms, which helps to monitor the acute attack and condition fluctuation of allergic rhinitis and asthma in real time.

[0054] The symptom records are the symptom manifestations of the patient in daily life, such as nasal symptoms (such as the degree of nasal congestion, the intensity of nasal itching, etc.), airway symptoms (such as the frequency of dyspnea attack, the degree of chest tightness, etc.), etc., which are filled in by the patient using a mobile phone App, a program or other smart terminals. They are used to provide continuous tracking of the patient's subjective feelings and clinical manifestations, helping to evaluate the trend of the disease.

[0055] The clinical data include, but are not limited to, IgE (immunoglobulin E) level, lung capacity, peak expiratory flow rate, etc., which are obtained through professional medical examinations such as lung function detection and allergen skin prick test of the patient by the medical institution. They are used to objectively reflect the immune allergic state and lung function status of the patient, and are important basis for judging the pathogenesis, severity and treatment efficacy of allergic rhinitis-asthma syndrome.

[0056] The traditional Chinese medicine syndrome differentiation module is used to obtain traditional Chinese medicine diagnosis information, apply a traditional Chinese medicine theoretical framework to comprehensively analyze the patient health portrait and the traditional Chinese medicine diagnosis information, identify the patient's syndrome characteristics, and serve as the traditional Chinese medicine syndrome differentiation result.

[0057] The traditional Chinese medicine diagnosis information includes pulse diagnosis information and tongue diagnosis information. The traditional Chinese medicine theoretical framework is the basic thinking system of traditional Chinese medicine, mainly composed of interrelated theories such as yin-yang theory, zang-fu and meridian theory, qi-blood and body fluid theory, and syndrome differentiation and treatment theory, which explains the physiological and pathological phenomena and their change rules from the perspective of holism and syndrome differentiation, and is the theoretical basis for guiding clinical practice of traditional Chinese medicine.

[0058] The pulse condition diagnosis information includes pulse strength, pulse rhythm and pulse waveform, and is used to reflect the blood circulation condition and the function state of the viscera of the patient. In the allergic rhinitis-asthma syndrome, the pulse condition can help to determine the pathological changes such as deficiency, excess, cold, heat, Qi stagnation and phlegm dampness in the patient's body, so as to assist in identifying the syndrome types such as Qi deficiency, lung cold and phlegm dampness blocking the lung. The pulse condition diagnosis information is obtained by the intelligent pulse diagnosis instrument.

[0059] The tongue condition diagnosis information includes tongue shape, tongue color, fur color and tongue texture, and is used to reflect the cold, heat, dampness, dryness, heat toxin and function state of the viscera in the patient's body. For the allergic rhinitis-asthma syndrome, the tongue condition can reveal the function state of the viscera such as the lung, spleen and kidney, help to identify different syndrome types such as wind-cold, wind-heat, phlegm dampness and blood stasis, and guide the treatment of traditional Chinese medicine. The tongue condition diagnosis information is obtained by the intelligent tongue diagnosis instrument.

[0060] The method for identifying the syndrome type characteristics of the patient includes:

[0061] The method for identifying the syndrome type characteristics of the patient includes:

[0062] The method for constructing the resonance model of the TCM syndrome type includes:

[0063] The method for constructing the resonance model of the TCM syndrome type includes:

[0064] The historical analysis data in each set of historical data is converted into corresponding discrete labels respectively; all the historical data is subjected to clustering processing to obtain a plurality of second clusters, and a corresponding TCM syndrome type is set for each second cluster; wherein the TCM syndrome type is, for example, wind-cold binding lung syndrome, phlegm-dampness blocking lung syndrome, lung qi deficiency syndrome, etc., and each second cluster includes a plurality of different sets of historical data; the discrete labels and tongue diagnosis 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 value respectively, the quantity threshold value is preset by a person skilled in the art according to the actual situation; the discrete information with the information quantity greater than the quantity threshold value is marked as feature information, and the discrete information with the information quantity less than or equal to the quantity threshold value is not marked; the feature set of each TCM syndrome type is constituted according to the feature information of each second cluster; it should be noted that the DBSCAN algorithm is used for clustering processing in this embodiment, and the DBSCAN algorithm is prior art, and the specific process will not be described in detail here;

[0065] 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 are calculated; the product of the conditional probability and the mutual information of the corresponding feature information is taken as the unit resonance intensity of the corresponding feature information; the sum of the unit resonance intensities of the corresponding TCM syndrome types is taken as the resonance intensity of the corresponding TCM syndrome type; the corresponding discrete information is obtained according to the patient health portrait and the TCM diagnosis information input into the TCM syndrome resonance model, and a variable set is constituted; the matching degree between the variable set and each feature set is calculated; based on the matching degree and the resonance intensity, the confidence of the variable set belonging to each TCM syndrome type is calculated; it should be noted that the calculation methods of the conditional probability and the mutual information are prior art, and the specific calculation process will not be described in detail here.

[0066] The calculation method of the matching degree is: comparing the variable set with the feature set to determine the occurrence coefficient of each discrete information in the variable set; the product of the occurrence coefficient of each discrete information in the variable set and the corresponding unit resonance intensity is added in sequence to obtain the matching degree; the determination method of the occurrence coefficient is: if the discrete information in the variable set exists in the feature set, the occurrence coefficient of the corresponding discrete information is determined as 1, and 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 as 0.

[0067] The calculation method of the confidence is: the product of the matching degree and the resonance intensity of the corresponding TCM syndrome type is taken as the local confidence; the sum of all local confidences is taken as the total confidence; the ratio of each local confidence to the total confidence is taken as the confidence of the corresponding TCM syndrome type.

[0068] The western medicine diagnosis module is configured to analyze objective medical indicators of the patient health portrait, identify abnormal medical indicators, diagnose diseases of the patient based on the abnormal medical indicators, and evaluate corresponding comprehensive clinical manifestations. The western medicine diagnosis result is formed based on the disease diagnosis result and the corresponding comprehensive clinical manifestations.

[0069] The method for identifying abnormal medical indicators includes:

[0070] The patient health portrait formed in real time is marked as real-time data, and the patient health portrait in the historical data and the real-time data are taken as a patient data set. The same type of data in the patient data set is taken as a set of index sets, and the data in each set of index sets is sorted in ascending order to generate an index sequence. The empirical distribution value of each data in the real-time data in the corresponding index sequence is calculated in turn, and each empirical distribution value is compared with the corresponding preset distribution threshold value.

[0071] The distribution threshold value includes a low-end threshold value and a high-end threshold value, and the distribution threshold values corresponding to different index sets are different and are set in advance by a person skilled in the art according to actual medical experience.

[0072] If the empirical distribution value is between the corresponding low-end threshold value and high-end threshold value, the corresponding data is not taken as an abnormal medical indicator.

[0073] If the empirical distribution value is greater than the corresponding high-end threshold value or less than the corresponding low-end threshold value, the corresponding data is taken as an abnormal medical indicator.

[0074] The calculation method of the empirical distribution value is to obtain the data bit (i.e., the ranking of the data in the index sequence) of the data in the corresponding index sequence, and count the number of data in the index sequence. The ratio of the data bit to the number of data is taken as the empirical distribution value.

[0075] The method for diagnosing diseases of the patient based on the abnormal medical indicators includes:

[0076] Each index in the abnormal medical indicators is converted into the membership degree of each discrete label corresponding thereto by a fuzzification technique. The fuzzification technique is a process of converting an accurate numerical value into the membership degree corresponding to a fuzzy set. The fuzzification technique may be, for example, a triangular membership function, a trapezoidal membership function, or the like.

[0077] A fuzzy causal network is defined. The fuzzy causal network is defined according to expert knowledge or related literature. The fuzzy causal network includes nodes and connecting edges. The connecting edges are located between two nodes. The nodes represent abnormal medical indicators or disease names. The connecting edges are located between two nodes and represent fuzzy rules between the two nodes. For example, if the two nodes are respiratory flow and asthma, the fuzzy rule is: if the corresponding flow of the respiratory flow is small, the membership degree of asthma is high.

[0078] Each abnormal medical indicator after the fuzzification processing is taken as an input, is associated with a corresponding node in the fuzzy causal network respectively, and is matched according to the fuzzy rules in the fuzzy causal network, a fuzzy reasoning method (such as a Mamdani fuzzy reasoning model, a Sugeno fuzzy reasoning model, etc.) is used for fuzzy reasoning, a fuzzy reasoning result is obtained, the fuzzy reasoning result includes membership degrees corresponding to different disease names; a disease name with a membership degree greater than a preset membership threshold is taken as a disease diagnosis result; the disease name is, for example, allergic rhinitis, asthma, chronic sinusitis, etc., and the membership threshold is preset by a person skilled in the art according to actual conditions.

[0079] The method for evaluating the comprehensive clinical manifestations includes:

[0080] Different digital labels are set for different disease names, and are marked as disease labels; the disease label corresponding to the disease diagnosis result and the abnormal medical indicator are input into the trained comprehensive evaluation model to obtain comprehensive clinical manifestations, the comprehensive clinical manifestations include disease severity, airway reactivity and inflammation state; wherein, the airway reactivity represents the sensitivity and reaction intensity of the airway to stimulants (such as allergens, cold air, exercise, etc.), and the inflammation state represents the degree of inflammatory reaction existing in the airway or lung;

[0081] 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 a plurality of neurons, each neuron is connected with a next layer of neurons, and the connection includes a weight, which determines 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 prior art, and the specific training process will not be described in detail here.

[0082] The comprehensive diagnosis module is used for cross-validation of the TCM syndrome differentiation result and the western medicine diagnosis result to obtain a comprehensive diagnosis result.

[0083] The method for obtaining the comprehensive diagnosis result includes:

[0084] The preset Chinese-Western mapping table includes the correlation between each TCM syndrome type and each disease name. The construction method of the Chinese-Western mapping table is that the person skilled in the art collects clinical cases containing double diagnosis information of TCM syndrome type and disease name, that is, the TCM syndrome type and disease name of each patient are recorded in each clinical case. The clinical cases corresponding to the same TCM syndrome type are taken as a set of case collection, the number of occurrences of each disease name in each set of case collection is counted and marked as a mapping number, the total number of occurrences of all disease names in each set of case collection is counted and marked as a mapping total number, the ratio of each mapping number to the corresponding mapping total number is calculated in turn to obtain a mapping frequency, each mapping frequency is taken in turn as the correlation between the corresponding TCM syndrome type and the corresponding disease name, and the Chinese-Western mapping table is constructed according to all correlations. The TCM syndrome type and the disease name in the Chinese-Western mapping table are both related to allergic rhinitis asthma syndrome.

[0085] According to the Chinese-Western mapping table, the correlation between each TCM syndrome type in the TCM syndrome differentiation result and each disease name in the Western medical diagnosis result is obtained in turn, and the maximum correlation corresponding to each TCM syndrome type and disease name is selected respectively (that is, the maximum correlation with the largest value is selected for each TCM syndrome type, and the maximum correlation with the largest value is also selected for each disease name).

[0086] The average correlation is obtained by mean processing all the maximum correlations. The average correlation is compared with a preset correlation threshold, and the correlation threshold is preset by the person skilled in the art according to the distribution of the correlation in the Chinese-Western mapping table. If the average correlation is greater than the correlation threshold, the cross-validation is successful, and the TCM syndrome differentiation result and the Western medical diagnosis result form a comprehensive diagnosis result. If the average correlation is less than or equal to the correlation threshold, the cross-validation fails, and the medical staff is prompted to review the TCM syndrome differentiation result and the Western medical diagnosis result.

[0087] It should be noted that the reason for cross-validation of the TCM syndrome differentiation result and the Western medical diagnosis result is that the correspondence between the two different medical systems is quantified to evaluate the consistency and rationality of the diagnosis results, thereby improving the accuracy and reliability of the diagnosis, promoting the scientific decision-making of the combination of traditional Chinese and Western medicine, and ensuring that the comprehensive diagnosis result is more comprehensive and effective.

[0088] The prescription generation module is used to obtain patient individualization factors and dynamically generate a personalized traditional Chinese medicine prescription in combination with the comprehensive diagnosis result.

[0089] The method for dynamically generating a personalized traditional Chinese medicine prescription comprises:

[0090] The skilled person in the art constructs a comprehensive traditional Chinese medicine knowledge graph by integrating information from classic prescription libraries (i.e., a collection of classic traditional Chinese medicine prescriptions recorded in medical books), modern traditional Chinese medicine literature (i.e., traditional Chinese medicine research papers, monographs, etc.), and traditional Chinese medicine patent databases (i.e., databases that collect all kinds of patent information related to traditional Chinese medicine prescriptions), etc. The knowledge graph is prior art, and the specific construction process will not be described in detail here.

[0091] According to the comprehensive diagnosis result, the candidate prescription of each group is obtained from the comprehensive traditional Chinese medicine knowledge graph; The candidate prescription of each group is obtained from the comprehensive traditional Chinese medicine knowledge graph; The candidate prescription of each group is obtained from the comprehensive traditional Chinese medicine knowledge graph; The candidate prescription of each group is obtained from the comprehensive traditional Chinese medicine knowledge graph; And Both are integers greater than 1. ; The medication regimen of each group is established by the skilled person in the art according to the patient's health portrait.

[0092] According to the patient's individualized factors and the patient's health portrait, a pharmacokinetic model is constructed. 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 according to the matching results of the symptom time characteristics and the pharmacokinetic characteristics of each group, the drug-symptom time matching index corresponding to each candidate prescription is calculated in turn. The candidate prescription with the largest drug-symptom time matching index is taken as the individualized traditional Chinese medicine prescription.

[0093] The patient's individualized factors include body characteristics and past medication reactions. Body characteristics include the patient's age, gender, and weight, and past medication reactions include drug adverse reaction history and drug sensitivity. Drug adverse reaction history 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 manifests as the same dose of drug may produce different intensities of effect in different patients. For example, some patients are particularly sensitive to sedatives, and even a small dose can produce a significant effect, while some patients may need a larger dose to achieve the desired therapeutic effect. Patient individualized factors are obtained through medical history records, clinical assessment, laboratory testing, etc.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] Methods for calculating drug-symptom time matching indicators include:

[0099] 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;

[0100] The preset weight set includes weight coefficients corresponding to the time coincidence degree and the drug efficacy coverage rate, which are preset by a person skilled in the art according to actual conditions; the time coincidence degree and the drug efficacy coverage rate are weighted and summed based on the weight set to obtain the drug-symptom time matching index.

[0101] The method for calculating the time coincidence degree according to the comparison result includes:

[0102] If the comparison result is that the actual drug efficacy start time is earlier than or equal to the symptom appearance time, the time coincidence degree is If the comparison result is that the actual drug efficacy start time is later than the symptom appearance time, the method for calculating the time coincidence degree is: taking the difference between the actual drug efficacy start time and the symptom appearance time as a time difference value; taking the ratio of the time difference value to the preset maximum acceptable delay as a response delay rate; and taking the difference between 1 and the response delay rate as the time coincidence degree.

[0103] It should be noted that the value range of the time coincidence degree is Therefore, when the response delay rate is greater than 1, the time coincidence degree is 0.

[0104] The method for calculating the drug efficacy coverage rate according to the matching result includes:

[0105] Taking the ratio of the matching result to the symptom appearance time as the drug efficacy coverage rate; the matching result is the length of the time period overlapping between the drug efficacy maintenance period and the symptom maintenance period.

[0106] The prescription optimization module is configured to dynamically acquire an environmental perception factor and intelligently optimize the personalized traditional Chinese medicine prescription based on the environmental perception factor.

[0107] The environmental perception factor includes a climate seasonal factor and an environmental monitoring factor.

[0108] The climate seasonal factor includes a current season and seasonal pathogenic factors.

[0109] The current season is the current seasonal stage, each season has specific climate characteristics and effects on the human body, and traditional Chinese medicine believes that the physiological functions of the human body will adjust with seasonal changes, such as spring promoting growth, summer promoting growth, autumn promoting convergence, and winter promoting concealment; the current season is obtained by automatically judging the current date, and is usually divided according to months or solar terms.

[0110] The seasonal pathogenic factor refers to a pathogenic factor that occurs or prevails with seasonal changes and has specific pathogenic properties. In spring, wind is the main pathogenic factor, which can easily cause wind-cold and wind-heat diseases. In summer, heat is the main pathogenic factor, which can easily cause heat and damp-heat diseases. In autumn, dryness is the main pathogenic factor, which can easily cause dryness and fluid loss diseases. In winter, cold is the main pathogenic factor, which can easily cause cold stagnation diseases. The seasonal pathogenic factor characteristics are obtained from the pre-established TCM theoretical knowledge base of the current season by the skilled person in the art, which includes the dominant exogenous pathogenic factors in different seasons.

[0111] The environmental monitoring factors include pollen concentration and air quality index.

[0112] The pollen concentration is the content level of various types of plant pollen in the air, such as tree pollen (e.g., pine, birch, etc.), herb pollen (e.g., grass, weeds, etc.), etc. High pollen concentration can trigger allergic reactions, such as allergic rhinitis, asthma, etc., and the anti-allergic and dispelling wind and evil drug ingredients need to be considered in the personalized traditional Chinese medicine prescription. The pollen concentration is obtained by accessing the pollen monitoring network API provided by meteorological agencies, disease control centers, or third-party pollen monitoring platforms, which supports returning pollen concentration by region and time.

[0113] The air quality index refers to a comprehensive indicator that measures the degree of air pollution. When the air quality is not good, the lung-clearing, detoxifying, and fluid-protecting drug ingredients need to be added in the personalized traditional Chinese medicine prescription. The air quality index is obtained by accessing the air quality monitoring API publicly provided by environmental protection departments or local environmental monitoring agencies.

[0114] The method for intelligently optimizing the personalized traditional Chinese medicine prescription includes:

[0115] Combining the environmental perception factors with the comprehensive diagnosis results to form comprehensive environmental diagnosis information; according to the comprehensive environmental diagnosis information and the comprehensive traditional Chinese medicine knowledge graph, re-obtaining the candidate prescriptions, and marking them as environment-adaptive prescriptions, which is an integer greater than 1; inputting each environment-adaptive prescription into the pharmacokinetic model to obtain the pharmacokinetic characteristics corresponding to each environment-adaptive prescription;

[0116] According to the comprehensive environmental diagnosis information, dynamically predicting the change rule of the symptom time characteristics to obtain the environmental correction characteristics (i.e., the symptom time characteristics under the influence of environmental perception factors); according to the matching results of the environmental correction characteristics and each group of pharmacokinetic characteristics, sequentially calculating the drug-symptom time matching index corresponding to each environment-adaptive prescription; intelligently optimizing the personalized traditional Chinese medicine prescription according to the environment-adaptive prescription with the largest drug-symptom time matching index.

[0117] The method for dynamically predicting the change rule of the symptom time characteristics includes:

[0118] Different digital labels are set for different TCM syndromes, current seasons and seasonal pathogenic factors, and are marked as prediction labels; the disease names in the comprehensive environmental diagnosis information are replaced by corresponding disease labels, and the TCM syndromes, current seasons and seasonal pathogenic factors are replaced by corresponding prediction labels; the replaced comprehensive environmental diagnosis information is input into the trained variability prediction model to predict the time characteristic variability, and the variability prediction model is a deep neural network model; based on the time characteristic variability, the symptom time characteristics are dynamically adjusted to obtain environmental correction characteristics;

[0119] The time characteristic variability is an index for measuring the deviation degree of the patient's symptom time characteristics caused by environmental perception factors; the time characteristic variability includes the variability corresponding to the symptom onset time and the symptom cycle; the method for dynamically adjusting the symptom time characteristics based on the time characteristic variability is that the product of each characteristic in the symptom time characteristics and the corresponding variability in the time characteristic variability is taken as the variability of each characteristic in the symptom time characteristics; and the sum of each characteristic in the symptom time characteristics and the corresponding variability is taken as the environmental correction characteristics.

[0120] For example, the symptom onset time in the symptom time characteristics corresponding to the patient is 8 am, and the predicted time characteristic variability is Therefore, the variability of the symptom onset time is The symptom onset time in the environmental correction characteristics is 6 am.

[0121] The embodiment adopts the method of combining TCM differentiation with western medicine diagnosis, integrates the TCM and western medicine diagnosis systems, realizes comprehensive analysis of the patient's syndrome characteristics and disease diagnosis by constructing a TCM syndrome resonance model and a fuzzy causal network, and improves the comprehensiveness and accuracy of diagnosis; based on the patient's health portrait and TCM diagnosis information, a personalized traditional Chinese medicine prescription is dynamically generated, and pharmacokinetic modeling is performed in combination with the patient's individual factors, which can more accurately predict the action characteristics of traditional Chinese medicine in the patient's body, so as to design a more personalized treatment plan that meets the actual needs of the patient; by dynamically obtaining environmental perception factors and integrating them with the comprehensive diagnosis results, the intelligent optimization of the personalized traditional Chinese medicine prescription can better adapt to the changing trend of the patient's symptoms in different environments, and improve the targeting and effectiveness of traditional Chinese medicine treatment; the advantages of traditional Chinese medicine in regulating constitution and preventing recurrence are fully utilized, and through the innovative technical means of integration of TCM and western medicine, personalized medication and environmental perception, intelligent support is provided for the whole process of TCM diagnosis and treatment of allergic rhinitis asthma syndrome, thereby effectively improving work efficiency, diagnosis and treatment quality and treatment effect, reducing adverse reactions, and providing a more scientific and effective TCM treatment plan for patients.

[0122] Embodiment 2

[0123] The application also provides an electronic device. The electronic device can include one or more processors and one or more memories. The memory stores computer readable code which, when executed by the one or more processors, can perform the allergic rhinitis-asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment as described above.

[0124] The method or system according to the embodiments of the application can also be implemented by means of the architecture of the electronic device shown in the application. The electronic device can 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 ROM or hard disk, can store the allergic rhinitis-asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment provided by the application. Further, the electronic device can also include a user interface. Of course, the architecture shown in the application is only exemplary, and when implementing different devices, one or more components of the electronic device shown in the application can be omitted according to actual needs.

[0125] Embodiment 3

[0126] One embodiment of the application discloses a computer readable storage medium. The computer readable storage medium stores computer readable instructions. When the computer readable instructions are executed by a processor, the allergic rhinitis-asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to the embodiments of the application described with reference to the above figures can be executed. The storage medium includes but is not limited to, for example, volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and cache memory, etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0127] In addition, according to the embodiments of the application, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, the application provides a non-transitory machine readable storage medium storing machine readable instructions executable by a processor to perform instructions corresponding to the method steps provided by the application, for example: the allergic rhinitis-asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment. When the computer program is executed by a central processing unit (CPU), the above functions defined in the method of the application are executed.

[0128] The above merely describes preferred embodiments of the present application, and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art will appreciate that the technical solutions described in the foregoing embodiments can be modified or equivalent replacements can be made to some technical features thereof. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall fall within the scope of protection of the present application.

[0129] It should be noted that, in this document, the terms "comprising", "containing", or any other similar term are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not only include those elements, but also includes other elements not explicitly listed, or further includes elements inherent in such a process, method, article, or apparatus. Without more limitations, the element defined by the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0130] In the description of the present application, it should be understood that the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0131] In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0132] In the description of the present application, the meaning of "several" is one or more, and the meaning of "a large number" is two or more.

[0133] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0134] The formula of the present specification is a dimensionless value, and the formula is obtained by collecting a large amount of data to simulate a formula of the most recent real situation. The preset parameters and threshold values in the formula are set by those skilled in the art according to the actual situation.

[0135] While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the application. The scope of the application is not to be limited by the embodiments shown and described, but only 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 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; 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 assigned to 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. 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 Mark the patient health profile formed in real time as real-time data, and use the patient health profile in historical data and real-time data as the patient data set; The same type of data in the patient data set is taken as a set of indicator sets, and the data in each indicator set is 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 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.

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 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.

6. The allergic rhinitis and asthma syndrome monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 5, 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.

7. The allergic rhinitis and asthma syndrome condition monitoring and diagnosis system for traditional Chinese medicine treatment according to claim 6, 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.

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 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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