43 results about "Syndrome type" patented technology

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 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 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 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 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.

The invention discloses a traditional Chinese medicine auxiliary diagnosis and treatment model correction method based on dynamic confidence coefficient calibration, and the method comprises the following steps: constructing a traditional Chinese medicine auxiliary diagnosis and treatment model, outputting a corresponding syndrome type according to the symptom of a patient, carrying out the frequency statistics of the syndrome types of a famous medical experience knowledge base, taking the syndrome type appearing at a high frequency as a common syndrome, and carrying out the correction of the traditional Chinese medicine auxiliary diagnosis and treatment model. The syndrome type of low frequency is rare; confidence coefficient smoothing is applied to the diagnosis result of the model predicated as the common certificate, and excessive confidence of the common certificate is inhibited; the calibration intensity of the dialectical confidence coefficient calibration module is dynamically adjusted according to an iteration process of model training; a calibrated model is utilized to generate a pseudo tag on a real-time clinical case library without a tag, the pseudo tag is added into a training set, the traditional Chinese medicine auxiliary diagnosis and treatment model is iteratively optimized, and the diagnosis accuracy of the model in a complex clinical situation is improved by inhibiting excessive confidence of common syndromes and dynamically adjusting the correction strength according to the model state. A large amount of unlabeled clinical data can be effectively utilized, and dependence on expensive labeled data is reduced.

The invention discloses a prescription preparation method and system based on artificial intelligence, a medium and equipment, and relates to the technical field of intelligent dispensing, and the method comprises the steps: obtaining a historical traditional Chinese medicine case text, and extracting a medical entity in the traditional Chinese medicine case text; based on the medical entity, determining a corresponding disease name in combination with a large language model, and determining a syndrome type result by performing context analysis on the medical entity and in combination with the disease name and a four-diagnosis-combined-parameter principle of traditional Chinese medicine; determining a treatment rule result according to a syndrome type result; generating a preliminary prescription result based on the syndrome type result and the treatment rule result; the generated preliminary prescription result is scored by introducing a large language model, a scoring result is obtained, and when the scoring result is larger than or equal to a preset threshold value, a final prescription preparation result is output; otherwise, generating a structured suggestion, and generating the prescription again according to the structured suggestion in combination with the syndrome type result and the rule result until the scoring result meets a preset threshold value, and obtaining a final prescription preparation result.

The invention discloses a children pneumonia auscultation sound and traditional Chinese medicine diagnosis data association method and device and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: collecting heart and lung auscultation sound signals of a to-be-diagnosed children, determining the characterization of the auscultation sound in western medicine auxiliary examination corresponding to the auscultation sound signals, and determining the diagnosis data of the children pneumonia auscultation sound; the western medicine physical signs comprise the characterization of auscultation sound; determining traditional Chinese medicine syndrome types in traditional Chinese medicine syndrome differentiation types corresponding to the characterization of the auscultation sound; and according to the western medicine physical signs and / or the traditional Chinese medicine syndrome type, determining traditional Chinese medicine medication recommendation of the to-be-diagnosed child. The diagnosis speed of children pneumonia is increased, objective basis is provided for traditional Chinese medicine diagnosis, associated parameters between traditional Chinese medicine and western medicine are established, and related basis is provided for combined diagnosis and medication of the traditional Chinese medicine and the western medicine.

The invention relates to the technical field of medical information processing, in particular to a traditional Chinese medicine syndrome type analysis method and device and a sleep disorder early intervention method and device.The traditional Chinese medicine syndrome type analysis method comprises the steps that an original feature data set containing tongue picture features and demographic information of a subject is obtained; performing feature expansion on the original feature data set by adopting a pre-constructed feature engineering scheme to obtain an expanded feature data set; the feature engineering scheme is determined according to traditional Chinese medicine theory priori knowledge in combination with a relationship between variables disclosed by exploratory analysis of a multi-source data set, and comprises a group of predefined feature construction rules; and inputting the original feature data set and the extended feature data set into a pre-trained syndrome type discrimination model to obtain a traditional Chinese medicine syndrome type discrimination result. And the traditional Chinese medicine syndrome type analysis accuracy is greatly improved.

The application discloses a kind of chronic disease multidimensional dynamic intervention management system of fusion ancient Chinese medicine diagnosis and treatment philosophy, it is related to chronic disease management technical field.The system includes data acquisition module, TCM syndrome differentiation and syndrome identification module, dynamic intervention scheme generation module and closed-loop management and iteration module.System is through collecting patient's four TCM diagnoses, constitution syndrome, character psychology and solstice etc multidimensional data, based on ancient Chinese medicine " holistic view " " treatment based on syndrome differentiation " And " disease from heart " Philosophy constructs algorithm model, dynamically identifies TCM syndrome and generates personalized intervention scheme of fusion diet, exercise and heart nature dredge.Meanwhile, according to patient execution feedback and data change carries out closed-loop iteration optimization.The application realizes the deep fusion of Chinese and western medicine data and the dynamic adjustment of intervention scheme, solves the problem of intervention static and ignoring psychological cause in prior art, significantly improves the accuracy of chronic disease management and patient compliance.

The invention discloses a traditional Chinese medicine syndrome type classification method and device. The method comprises the following steps: S1, acquiring medical case short text data and medical case long text data; s2, inputting the medical case short text data into a multi-scale image feature fused image convolutional neural network traditional Chinese medicine syndrome type classification model to obtain a first traditional Chinese medicine syndrome type classification result; s3, inputting the medical case long text data into the multi-scale text feature fused traditional Chinese medicine syndrome type classification model to obtain a second traditional Chinese medicine syndrome type classification result; and S4, fusing the first traditional Chinese medicine syndrome type classification result and the second traditional Chinese medicine syndrome type classification result to obtain a final traditional Chinese medicine syndrome type classification result. By adopting the technical scheme, the syndrome type classification accuracy is improved, the fusion of traditional Chinese medicine and artificial intelligence is promoted, and the modern development of traditional Chinese medicine is accelerated.

The invention relates to a traditional Chinese medicine rehabilitation support system suitable for chronic stomach illness, which comprises the following steps: determining the related core information of the symptom type of a patient by using a traditional Chinese medicine dialectical evaluation module and a multi-aspect information fusion method; in combination with a traditional Chinese medicine body mass table, a symptom score table and a life habit questionnaire, obtaining multi-aspect scores required by dialectical differentiation of the patient; through the patient information registration and management module, comprehensive recording and standardized management from patient case information, previous diagnosis and treatment history and auxiliary examination data to daily rehabilitation execution details are achieved, and data support is provided for making and dynamic adjustment of a personalized rehabilitation scheme; by integrating multi-angle information such as physique scores, symptom scores, living habit scores and medical history examination scores and combining a preset dialectical rule base and algorithm, matching of comprehensive dialectical scores and syndromes of patients is completed, and the problem of syndrome type misjudgment caused by high subjectivity of individual dialectical subjectivity and limited resources of primary doctors in traditional Chinese medicine rehabilitation is effectively solved.