53 results about "Syndrome type" patented technology

The invention belongs to the technical field of traditional Chinese medicine syndrome type classification, and discloses a traditional Chinese medicine syndrome type library construction method and system based on a convolutional neural network, and the method comprises the steps: constructing a corpus for mapping traditional Chinese medicine semantics and a dynamic semantic analysis framework, and carrying out the data enhancement preprocessing of the corpus; the method comprises the following steps: acquiring data, cleaning the acquired data, and removing repeated, missing or abnormal data; constructing a convolutional neural network, and processing and outputting the input data; and constructing a traditional Chinese medicine syndrome type library based on the output syndrome types, and deploying the trained convolutional neural network in an online diagnosis and treatment system for automatic classification and storage. Key features can be automatically extracted from traditional Chinese medicine clinical data, the traditional Chinese medicine symptoms are classified into the corresponding traditional Chinese medicine syndromes by constructing the mapping relation between the traditional Chinese medicine symptoms and the syndromes and utilizing the convolutional neural network to learn the symptom features, a perfect traditional Chinese medicine syndrome knowledge base is formed, and scientific and efficient auxiliary decision support is provided for traditional Chinese medicine clinical diagnosis and treatment.

The invention discloses a traditional Chinese medicine syndrome type matching method based on cross-modal attention fusion and a knowledge graph, and the method comprises the steps: obtaining multi-modal diagnosis data of a patient, the multi-modal diagnosis data being used for representing four kinds of diagnosis information collected by a doctor through watching, smelling, asking and cutting, including visual diagnosis data, pulse condition time sequence data and text data; inputting the multi-modal diagnosis data into a trained intelligent traditional Chinese medicine analysis system to obtain a syndrome type matching result of the patient; the intelligent traditional Chinese medicine analysis system comprises a feature extraction and fusion module and an evidence fusion derivation module, and the feature extraction and fusion module is used for extracting features of different modal diagnosis data to obtain multi-modal diagnosis features. And the cross-modal attention operation module is used for carrying out cross-modal attention operation on the multi-modal diagnosis features to fuse the features of different modals to obtain a unified semantic representation, and the evidence fusion derivation module is used for generating an evidence type matching result according to the semantic representation. The method is high in accuracy and good in effect.

The invention relates to the technical field of adaptive control, in particular to a syndrome differentiation adaptive control system for intelligent traditional Chinese medicine treatment equipment, which comprises an environmental parameter acquisition unit for acquiring microenvironment parameters in real time and generating environmental compensation parameters; the moxibustion sense feedback input unit quantifies subjective moxibustion sense feedback of the patient; the syndrome differentiation and trend prediction unit is used for outputting dynamic syndrome type probability distribution and a syndrome evolution prediction sequence based on the traditional Chinese medicine knowledge graph; and the self-adaptive control decision unit is used for generating a final self-adaptive control instruction when the emergency safety condition is not triggered by integrating the environment compensation parameters, the moxibustion sense feedback, the syndrome type probability and the evolution prediction result. According to the system, three types of data sources are fused, a four-stage serial correction architecture is adopted, and multi-stage regulation and control are automatically completed in a treatment cycle, so that equipment is not out of alignment due to environmental fluctuation, downshift is performed no longer after scalding, and prescription change is performed no longer after symptom transformation, and therefore, temperature control precision improvement and manual intervention return-to-zero can be realized.

The invention discloses a state identification-based traditional Chinese medicine prescription intelligent recommendation method, a medium and equipment. The method comprises the following steps of: firstly, mapping a discrete symptom set into a trainable symptom embedding matrix; then, the relevance between symptoms is dynamically modeled through a multi-layer Transform encoder, and weighted fusion and nonlinear transformation of symptom features are achieved through an attention mechanism; and finally, after globally averaging and fusing the symptom characterization, inputting the symptom characterization into a three-level MLP network to sequentially generate a state element vector, symptom type probability distribution and traditional Chinese medicine recommendation probability distribution, and then outputting a recommended traditional Chinese medicine combination according to probability sorting. The correlation strength between symptoms is automatically learned through a Transform self-attention mechanism, dynamic characterization of the symptoms is achieved, a three-level MLP explicitly constructs a traditional Chinese medicine reasoning chain of'pathogenesis-syndrome type-prescription ', and the integrity of the syndrome differentiation process is ensured. According to the method, the accuracy of symptom identification, symptom type classification and prescription recommendation is remarkably improved.

The application provides a syndrome type classification method and device based on syndrome element decomposition, equipment and medium. The method analyzes the syndrome type name and syndrome type description of the to-be-classified syndrome type through a syndrome element prediction model, splits and predicts the main syndrome element and the secondary syndrome element of the to-be-classified syndrome type as the symptom characteristics of the to-be-classified syndrome type. The target feature vector of the to-be-classified syndrome type is subjected to similarity matching through the retrieval of the known feature vector of the known syndrome type, so that the known syndrome type similar to the feature of the to-be-classified syndrome type is searched in the known syndrome type library to complete the classification of the to-be-classified syndrome type. The application relates to the technical field of model prediction. The feature vector of the to-be-classified syndrome type is obtained through the syndrome element decomposition of the syndrome type, and the vector matching is performed with the known syndrome type, so that the matching between the syndrome types with different standard names and the same symptoms can be realized, the accuracy of the syndrome type matching is improved, and the classification accuracy between the syndrome types with different standards is improved.

The invention relates to the technical field of traditional Chinese medicine data processing, and particularly provides a method for obtaining traditional Chinese medicine data based on six-channel syndrome differentiation, a storage medium, equipment and a product. Matching the pathological keyword with a plurality of items of six-channel differentiation to obtain item information to which the physical symptom belongs; based on the item information, traditional Chinese medicine diagnosis and treatment data of the user are determined, and the traditional Chinese medicine diagnosis and treatment data comprise traditional Chinese medicine syndrome type information, traditional Chinese medicine treatment rules, six-channel syndrome differentiation results or recuperation prescriptions. Some embodiments of the application can automatically predict the traditional Chinese medicine diagnosis and treatment data for the user based on the six-channel syndrome differentiation, so that the user can know own conditions, and reference contents related to the six-channel syndrome differentiation can be provided for doctors.

The invention relates to the technical field of traditional Chinese medicine data processing, and particularly provides a method for obtaining traditional Chinese medicine data based on six-channel syndrome differentiation, a storage medium, equipment and a product, and the method can comprise the steps: obtaining questionnaire data of a personalized questionnaire generated based on user feature information, the user feature information comprises tongue condition information, face information, pulse condition information or palm information, and the questionnaire data represents symptom information existing in the user; obtaining item information matched with the questionnaire data from a six-channel dialectical item mapping table; based on the item information, traditional Chinese medicine diagnosis and treatment data of the user are determined, and the traditional Chinese medicine diagnosis and treatment data comprise traditional Chinese medicine syndrome type information, traditional Chinese medicine treatment rules, six-channel syndrome differentiation results or recuperation prescriptions. Some embodiments of the application can provide interrogation reference suggestions under six-channel syndrome differentiation for doctors.

The embodiment of the invention provides a user diagnosis and treatment information processing method, a program product, equipment and a storage medium. The method comprises the following steps: acquiring traditional Chinese medicine diagnosis and treatment information of a user and disease information of the user; the traditional Chinese medicine diagnosis and treatment information of the user comprises tongue diagnosis information, face diagnosis information, pulse diagnosis information and palm diagnosis information; the user disease information comprises user disease information and user symptom information; inputting the traditional Chinese medicine diagnosis and treatment information of the user into a trained information processing model to obtain output user prediction information; the user prediction information comprises a prediction syndrome element, a prediction symptom and a prediction cause of the user; matching a prediction syndrome type set hit by the disease information of the user from a syndrome type library; syndrome types corresponding to the diseases and symptoms corresponding to the syndrome types are recorded in the syndrome type library; determining user syndrome information from the prediction syndrome set by using the user prediction information; and the target prescription is matched from the prescription library based on the user disease information and the user syndrome type information, so that the traditional Chinese medicine auxiliary diagnosis and treatment accuracy based on artificial intelligence is improved.

The invention provides a traditional Chinese medicine syndrome differentiation and typing establishment method for immune checkpoint inhibitor related cardiotoxicity, which comprises the following steps: formulating a traditional Chinese medicine syndrome questionnaire, and collecting and standardizing clinical syndromes; performing quantitative scoring on the collected traditional Chinese medicine syndrome questionnaire; performing syndrome type induction and constructing a traditional Chinese medicine syndrome differentiation typing model; and outputting a syndrome differentiation result according to the established traditional Chinese medicine syndrome differentiation typing model. By establishing the traditional Chinese medicine syndrome differentiation typing model, a personalized traditional Chinese and western medicine combined treatment scheme can be conveniently formulated for a patient clinically and subsequently.

The present invention belongs to the technical field of traditional Chinese medicine assisted diagnosis and treatment, and specifically discloses an assisted diagnosis and treatment system based on a traditional Chinese medicine large model. By receiving tongue image uploaded by patients at the same time period regularly, tongue image features of different tongue body regions are extracted. Thus, by using the tongue image features under time series, tongue image change curves are generated, and the syndrome type evolution path is output by using the tongue image - syndrome type model. Then, the clinical indicators of the patients in the same time series are associated with the syndrome type evolution path to form a syndrome type - disease association matrix. Based on this, a prescription compatibility scheme is recommended to ensure that the treatment plan is not only based on the syndrome type, but also fully considers the specific pathological mechanism and clinical manifestations, avoiding the disconnection between the treatment plan and the actual condition, realizing more accurate and personalized traditional Chinese medicine assisted diagnosis and treatment. In addition, automated data processing and analysis reduce manual intervention, improve the diagnosis and treatment efficiency, and save medical resources.

The application relates to the technical field of traditional Chinese medicine intelligent diagnosis, and discloses a traditional Chinese medicine syndrome differentiation and treatment hierarchical reasoning system suitable for four-examination logic, which comprises a data acquisition module used for periodically collecting four-examination data of a user; an individualization module constructs an individualized health state topology based on multiple groups of four-examination data under a user health state; a state deviation calculation module calculates a deviation degree and a deviation direction vector of a current four-examination state relative to the topology; a state evolution module internally has a yin-yang growth and decline model to predict a yin-yang state change trajectory with the current state as an initial condition; a hierarchical reasoning module comprises multiple syndrome differentiation sub-layers, each layer takes the deviation degree and the deviation direction vector as a weight factor to be integrated into reasoning and outputs a syndrome differentiation result; and a latent syndrome identification module matches a latent syndrome type according to the deviation direction vector, generates an early warning signal in combination with the deviation degree and the predicted trajectory, solves the problem of four-examination information time sequence loss, and realizes from already-ill syndrome differentiation to latent syndrome early warning.

The invention relates to the field of medical information processing and artificial intelligence, in particular to a gynecological disease intelligent diagnosis method and system based on traditional Chinese medicine syndrome differentiation, and the method comprises the steps: S1, receiving symptom / tongue condition / pulse condition multi-modal data containing a menstrual phase; s2, quality control and supplement; s3, carrying out image / time sequence / text coding and cross-modal and phase alignment; s4, loading a dialectical knowledge graph; s5, generating fusion features under the priori consistency and graph Laplacian regularization; s6, risk and syndrome type matching is calculated, and a consistency score is obtained according to the compatibility matrix; s7, generating a traceability evidence chain containing a source, a timestamp and a phase, and calculating Hash; s8, outputting the scores and the evidence chain, and writing the scores and the evidence chain into a non-rewritable log; the method is only used for clinical decision support. According to the method, a'phase alignment + prior constraint fusion 'mechanism is constructed, so that the result fluctuation caused by menstrual phase disturbance is remarkably reduced, the comparability and consistency of cross-time and cross-modal are improved, and the stability and compliance of clinical decision support are guaranteed by traceable evidence.

This invention discloses a traditional Chinese medicine composition for the prevention and / or treatment of type 2 cardiorenal syndrome and its application. By weight, the raw materials of the traditional Chinese medicine composition include: Astragalus membranaceus 15-30 parts, Paeonia lactiflora 10-20 parts, Saposhnikovia divaricata 5-10 parts, Leonurus japonicus 9-30 parts, Massa fermentata 9-30 parts, Poria cocos 10-30 parts, Cinnamomum cassia twig 9-30 parts, Atractylodes macrocephala 10-30 parts, and Glycyrrhiza uralensis 2-10 parts. This traditional Chinese medicine composition is mainly targeted at patients with early-stage renal damage in type 2 cardiorenal syndrome due to spleen-yang deficiency and blood stasis obstructing the collaterals. It utilizes a combination of various traditional Chinese medicines, whose active ingredients synergistically enhance each other, thereby achieving the therapeutic effect of improving early-stage renal damage after chronic heart failure and delaying the pathological progression of type 2 cardiorenal syndrome.

The invention discloses a traditional Chinese medicine syndrome differentiation method and device based on difficult text mining, a storage medium and electronic equipment, belongs to the technical field of natural language processing and the field of medical health information processing, and aims to solve the technical problem of how to distribute corresponding traditional Chinese medicine syndrome types for clinical texts of patients by using a natural language processing technology. According to the technical scheme, the traditional Chinese medicine syndrome differentiation method and device based on difficult text mining are adopted, and the method comprises the following steps that S1, a traditional Chinese medicine syndrome differentiation model training data set is constructed; s2, constructing a traditional Chinese medicine syndrome differentiation model; and S3, training the traditional Chinese medicine syndrome differentiation model. And (2) a traditional Chinese medicine syndrome differentiation device based on difficult text mining, wherein the device comprises a traditional Chinese medicine syndrome differentiation training data set construction unit, a traditional Chinese medicine syndrome differentiation model construction unit and a traditional Chinese medicine syndrome differentiation model training unit.

The application relates to the technical field of artificial intelligence, and particularly discloses a syndrome type matching method, device and equipment and a storage medium, wherein the method comprises the following steps: acquiring a symptom sequence to be matched, mapping the symptom sequence to be matched by using a syndrome element knowledge base to obtain a corresponding first syndrome element list to be matched, the syndrome element knowledge base being constructed based on pre-obtained syndrome element experience knowledge; inputting the symptom sequence to be matched into a pre-trained syndrome element mapping model to obtain a second syndrome element list to be matched; integrating the first syndrome element list to be matched and the second syndrome element list to be matched to obtain a final syndrome element list to be matched; and performing similarity matching on the final syndrome element list to be matched and a known syndrome element list corresponding to each known syndrome type to obtain a matched target known syndrome type and output the matched target known syndrome type. The application combines the TCM syndrome element experience knowledge and the machine learning model, improves the accuracy of the syndrome type matching, and ensures the interpretability of the matching result in the TCM field.

The present application relates to the technical field of traditional Chinese medicine syndrome type classification, and particularly relates to a traditional Chinese medicine syndrome type classification and probability prediction method based on artificial intelligence, which comprises: normalizing scattered data, natural language text data and image data related to patient syndromes to obtain normalized data, and the collection of each normalized data is a normalized data set; inputting the normalized data set into a trained syndrome type classification model based on Transform to obtain each syndrome probability corresponding to the syndromes; the model sequentially comprises: a patient information multi-modal embedding layer, a first self-attention layer, and a first linear mapping+Softmax function calculation layer; after the normalized data set in the patient information multi-modal embedding layer is input into the first self-attention layer for attention calculation, each syndrome probability is calculated through the function calculation layer; wherein the patient information multi-modal embedding layer is used for storing the normalized data set. The intelligent classification and probability prediction of traditional Chinese medicine syndrome types are realized.

The invention discloses a traditional Chinese medicine diagnosis question and answer based on deep learning, and relates to the technical field of traditional Chinese medicine, and the method comprises the steps: remotely obtaining tongue condition information, pulse condition information, complexion diagnosis information and auscultation information of a patient; the color and state of the patient can be remotely observed; the disease condition of the patient is obtained through language communication; wherein the disease conditions of the patient comprise consciousness symptoms, the incidence process, the treatment course, the daily life, the plain physique, the past medical history and the family medical history; constructing a diagnosis and treatment knowledge graph by analyzing related traditional Chinese medicine literatures and medical case contents; wherein the medical case content comprises the disease condition, tongue condition information, pulse condition information, complexion diagnosis information and auscultation information of the patient; and in combination with syndrome type classification of a traditional Chinese medicine theory, analyzing the constructed disease condition knowledge graph by using a deep learning model so as to intelligently classify and diagnose the disease condition of the patient.

The invention discloses a traditional Chinese medicine syndrome differentiation language model training and reasoning method based on natural language processing, and particularly relates to the technical field of medical information processing. The method comprises the following steps: performing sentence segmentation and symptom statement segmentation on a traditional Chinese medicine medical record text of a patient to construct a symptom statement sequence data set, and analyzing a co-occurrence relation and occurrence position distribution of symptom statements in a patient narrative context to generate context association features of the symptom statements; identifying functional role differences of the same symptom in different narrative contexts according to the context association features of the symptom statements to generate symptom context role annotation data; and dynamically redistributing the participation degree of the symptom characteristics in different symptom type reasoning processes based on symptom context role labeling data, carrying out constraint updating on the traditional Chinese medicine syndrome differentiation language model, and inputting a traditional Chinese medicine medical record text of a to-be-analyzed patient into the trained traditional Chinese medicine syndrome differentiation language model in a reasoning stage. And outputting a corresponding traditional Chinese medicine syndrome type judgment result.

The application provides an acupoint-syndrome correlation information processing method and device, a terminal device and a storage medium, and the method comprises the following steps: mapping a text to a corresponding node in a graph to obtain structured data; weighting entities in the text according to a pathological degree to obtain a weighting result; obtaining an entity weighting result according to a preset strategy and performing mapping to obtain a syndrome coding result; coding resistance data of acupoints to obtain a coding result and splicing the coding result with the syndrome coding result to obtain a feature vector; initializing a clustering center, iteratively calculating the distance between the feature vector and the clustering center, and assigning the feature vector to a cluster cluster to which the nearest clustering center belongs until a preset requirement is reached, and outputting a syndrome type judgment result of the feature vector. The application standardizes and fuses the expression of medical record texts and acupoint resistance data, constructs a three-dimensional mapping relationship of “symptoms-syndrome type-acupoints”, and can improve the effectiveness and accuracy of cervical spondylosis syndrome type identification.

The application discloses application of a composition in a synergist of a medicine for treating depression, wherein the composition is made of Rubia cordifolia, Taxillus delavayi, Pyrrosia lingua, Oldenlandia diffusa and Achyranthes bidentata, and the medicine for treating depression is made of Astragalus membranaceus, Atractylodes macrocephala, Poria cocos, Codonopsis pilosula, prepared Aconitum (black smooth tablet), Cornus officinalis, Salvia miltiorrhiza and Motherwort. The medicine combination prepared from the composition and the medicine for treating depression can significantly improve the depressive behavior of a depressive mouse, relieve the symptom of interest deficiency, and increase the content of a neurotransmitter in the brain of the depressive mouse. Further clinical tests find that the medicine combination has a significant clinical curative effect on various Chinese medical syndrome types of depression, such as liver depression and qi stagnation type, liver depression and fire type, liver depression and spleen deficiency type, phlegm and qi stagnation type, heart and spleen deficiency type, and kidney deficiency and liver depression type, and shows a good anti-depression effect, so the medicine combination has a wide application prospect.

The invention discloses a dialectical acupoint selection method and a dialectical acupoint selection system for treating senile intractable insomnia by using a sleeve type wrist-ankle needle, which comprises the following steps of: acquiring symptom and sign information of a patient in multiple dimensions, screening a target syndrome type range by comparing five syndrome types, determining a candidate acupoint selection area by combining meridian circulation and wrist-ankle needle partition positioning, screening a preset acupoint through acupoint specificity analysis, and selecting a target acupoint selection area according to the preset acupoint selection area. The acupuncture angle, depth and operation sequence are planned, and finally a personalized scheme is formed; the system comprises six units including a symptom and sign acquisition unit, a syndrome type matching analysis unit, a meridian partition association mapping unit, a preset acupoint screening evaluation unit, an acupuncture parameter planning unit and a scheme integration output unit, and all the units are coordinated and linked to achieve whole-process standardized operation. The method and the system take dialectical therapy as a core, establish systematic association of syndrome types, meridians and collaterals, acupuncture points and acupuncture parameters, improve the accuracy and consistency of acupuncture point selection, provide scientific and normative personalized treatment support for senile intractable insomnia, and are suitable for traditional Chinese medicine clinical treatment scenes.

The embodiment of the invention provides a health care method based on acupuncture points, a program product, equipment and a storage medium. The method comprises the steps that syndrome differentiation treatment information of a patient and disease information of the patient are acquired; the syndrome differentiation treatment information comprises one or more of patient syndrome type information, patient symptom information and patient traditional Chinese medicine diagnosis and treatment information; the traditional Chinese medicine diagnosis and treatment information of the patient comprises one or more of tongue diagnosis information, face diagnosis information, pulse diagnosis information and palm diagnosis information; basic acupuncture points are determined according to the disease information of the patient, auxiliary acupuncture points are determined based on the syndrome differentiation and treatment information, and an acupuncture point set comprising the basic acupuncture points and the auxiliary acupuncture points is obtained; determining an acupoint stimulation strategy based on the syndrome differentiation and treatment information, wherein the acupoint stimulation strategy comprises one or more of an acupoint stimulation mode, stimulation time and an operation method; and outputting a personalized acupoint health-care scheme including the acupoint set and the acupoint stimulation strategy. According to the personalized academic health-care scheme, the patient can be subjected to health-care conditioning according to the information such as the symptom type, the symptom, the tongue, the face, the pulse and the palm of the patient, and the health-care effect is improved.

The present invention provides a palm temperature monitor for Traditional Chinese Medicine (TCM) diagnosis. The monitor comprises an infrared sensor array that collects discrete palm temperature data; a temperature field reconstruction module that generates a continuous temperature field distribution; a TCM zoning module that divides viscera-related regions according to meridian maps; a dynamic coupling analysis module that calculates thermodynamic coupling parameters between regions; an abnormality diagnosis module that generates graded pathological indicators based on the coupling parameters; an environmental compensation module that corrects the discrete temperature data; a syndrome mapping module that matches the pathological indicators with a TCM syndrome database; and an output module that integrates the temperature field distribution with the syndrome matching results to generate a diagnostic report. This device can accurately reflect the functional status of the viscera, providing an objective and quantitative basis for TCM diagnosis, thereby improving diagnostic efficiency and accuracy.

The invention discloses a traditional Chinese medicine ointment formula for treating kidney deficiency and damp-heat syndrome type chronic glomerulonephritis as well as a preparation method and application thereof. The ointment formula is prepared from astragalus membranaceus, codonopsis pilosula, bighead atractylodes rhizome, donkey-hide gelatin, radix aconiti lateralis preparata, semen cuscutae, eucommia ulmoides, the root of kudzu vine, dried ginger, medicated leaven, rhizoma polygonati, gynostemma pentaphylla, teasel root, lucid ganoderma, divaricate saposhnikovia root, ligusticum wallichii, the root of bidentate achyranthes, parasitic loranthus, deer-horn glue, angelica sinensis, pulp of dogwood fruit, caulis spatholobi, gastrodia elata and pyrrosia lingua. According to the pathogenesis characteristics of the chronic glomerulonephritis, according to clinical practice, treatment based on syndrome differentiation, emphasis on tongue vein change, emphasis on combination of four diagnoses, mastering of yin and yang, and taking flat as a period; five internal organs are harmonized, and spleen and kidney are used as the basis; warm and clear effects are combined, and dynamic and static effects are combined; clinical test results show that after the ointment provided by the invention is used for treatment, the improvement condition of a treatment group is obviously superior to that of a control group, and the total effective rates of the treatment group and the control group in the treatment effect of the traditional Chinese medicine syndromes are 93.3% and 46.7% respectively; therefore, the ointment has a remarkable curative effect in the aspect of relieving the traditional Chinese medicine syndromes of the patients with the kidney-deficiency damp-heat syndrome type chronic nephritis.

This invention relates to the field of TCM medical information technology, and particularly to a method for generating TCM rehabilitation and nursing plans based on big data-driven syndrome differentiation. The method includes: collecting physiological parameters, medical records, and facial and tongue images to construct a standardized large dataset; using a semantic association model for feature decoupling; deriving syndrome types through syndrome differentiation logic algorithms and generating a syndrome differentiation report; matching the report to a virtual reality rehabilitation scenario; monitoring rehabilitation performance using sensing devices during training and triggering real-time plan adjustments; and applying an evolutionary prediction algorithm to simulate syndrome trends and output a full-cycle TCM rehabilitation and nursing plan. This invention achieves deep integration and closed-loop adjustment of TCM syndrome differentiation and virtual reality, significantly improving the targeting, compliance, and safety of rehabilitation and nursing care.

This invention belongs to the field of clinical efficacy evaluation technology, specifically relating to a method and system for evaluating the efficacy of oral antisleep granules combined with acupoint application in treating insomnia of the heart-kidney disharmony type. The method includes the following steps: selecting subjects to form an observation group and a control group; the control group receiving oral zopiclone tablets; the observation group receiving the same treatment as the control group, combined with oral antisleep granules and acupoint application; observing and comparing indicators: comparing the indicators of the control group before and after treatment with those of the observation group before and after treatment to obtain the efficacy difference between the two groups. The indicators include: a Traditional Chinese Medicine (TCM) syndrome score, where a scale is used to score difficulty falling asleep, shallow sleep with easy awakening / difficulty falling back asleep after waking, early awakening, and lower back and knee weakness. The efficacy evaluation method and system of this application can evaluate the efficacy of oral antisleep granules combined with acupoint application in treating insomnia of the heart-kidney disharmony type.

The invention provides a traditional Chinese medicine intelligent diagnosis system cooperatively driven by diseases and medicines. The traditional Chinese medicine intelligent diagnosis system comprises a data acquisition module, an intelligent diagnosis module and a result output module. The data acquisition module is used for acquiring to-be-diagnosed traditional Chinese medicine syndrome text data; the intelligent diagnosis module is used for carrying out intelligent analysis and judgment on traditional Chinese medicine syndrome text data by using a traditional Chinese medicine diagnosis model, and the traditional Chinese medicine diagnosis model firstly carries out deep feature extraction on an input text by using a semantic understanding unit constructed based on a BERT model to obtain semantic vector representation of syndromes; inputting the vector representation into a four-order asymmetric tensor coupling network constructed based on a professional knowledge base to carry out high-order reasoning and mapping, and finally generating corresponding relations between syndromes and diseases, prescriptions and medicinal materials; and the result output module is used for outputting syndrome types, diagnosis conclusions, treatment schemes and diagnosis reports. The invention provides a traditional Chinese medicine intelligent diagnosis system which is simple, rapid, efficient, objective and high in accuracy.

The invention discloses a traditional Chinese medicine cold-heat syndrome type identification method, device and system and a storage medium, and the method comprises the steps: S1, constructing a biological sample library according to the tongue coating flora of healthy people, cold-cold syndrome people and cold-heat syndrome people; s2, according to the biological sample library and the traditional Chinese medicine syndrome integral scale, constructing a cold-cold-heat syndrome classification model; and S3, inputting the to-be-processed tongue coating flora of the tested person into the cold and cold-heat syndrome classification model for traditional Chinese medicine cold-heat syndrome type identification. By adopting the technical scheme provided by the invention, an objective basis is provided for the judgment and curative effect evaluation of the cold-heat syndrome in the traditional Chinese medicine by detecting the tongue coating flora.

The invention provides a traditional Chinese medicine viscera disease non-contact identification method and system, and the method comprises the following steps: obtaining the index parameter information of the heart rate variability of a patient with the viscera disease in traditional Chinese medicine and a healthy population, and building a first sample set; data cleaning and standardization processing are conducted on the first sample set on the basis of a traditional Chinese medicine viscera disease knowledge base, a second sample set is obtained, and the traditional Chinese medicine viscera disease knowledge base comprises the mapping relation between abnormal indexes of heart rate variability and viscera disease syndromes; extracting an index feature vector of heart rate variability in the second sample set, and converting the traditional Chinese medicine viscera disease syndrome type into a traditional Chinese medicine syndrome type semantic feature vector based on a knowledge graph; fusing the index feature vector of the heart rate variability and the semantic feature vector of the traditional Chinese medicine syndrome type by adopting an attention mechanism to generate a multi-modal fusion feature vector set; according to the method, the heart rate variability features are fused with the traditional Chinese medicine symptom type semantic features to form the multi-modal feature information, the human body constitution features are accurately reflected, and the accuracy of symptom type identification is improved.

The invention relates to the technical field of traditional Chinese medicine tri-jiao symptom identification, and provides a traditional Chinese medicine tri-jiao symptom identification method and system based on a face video, and the method comprises the steps: collecting the face video, and extracting a remote photoelectric volume pulse wave; performing dynamic spectrum reconstruction; dividing upper, middle and lower focal dynamic frequency bands by using a time-varying boundary function, and calculating a power spectrum; detecting virtual-real syndrome type spectrum overlapping and performing self-adaptive separation by using a virtual-real conversion phase function to obtain a tri-focal syndrome feature; and inputting the features into a multi-path prediction decision model based on a tri-focal transmission rule, and fusing the path confidence to output a tri-focal symptom identification result. According to the method, the traditional Chinese medicine tri-focal theory and modern signal processing are fused, a time-varying boundary function is used for performing tri-focal frequency band dynamic division and virtual-real conversion of a phase function, accurate separation of syndrome characteristics is realized, parallel path prediction is performed based on a tri-focal transmission rule in combination with a multi-path prediction decision model, and the accuracy of path prediction is improved. And dynamically adjusting the confidence coefficient of each transmission path through a path weight fusion algorithm.