535results about "Alternative medicines" patented technology

The invention discloses an illness state tracking management system and method based on a lingual face diagnosis instrument, and belongs to the technical field of traditional Chinese medicine tongue diagnosis and modern information technology fusion. The system comprises a multi-modal data acquisition module, a data processing and analysis module and an augmented reality visualization module; according to the method, illness state tracking is achieved through the steps of multi-modal data acquisition, data preprocessing and feature fusion, personalized digital twinborn model establishment, augmented reality visualization presentation and the like, multi-dimensional data such as tongue picture macroscopic features and tongue surface microorganism distribution can be integrated, dynamic association between the data is revealed, the health state and the intervention effect are visually displayed, and the method is suitable for being popularized and applied. The method is suitable for the fields of traditional Chinese medicine health management and chronic disease monitoring.

The invention discloses a traditional Chinese medicine famous prescription and operation multi-agent collaborative consultation method and system. The system comprises a medical case knowledge base module, an expert knowledge base module, a medicine knowledge base module, a pre-differentiation module, a multi-agent diagnosis module and the like. The method comprises the following steps: constructing structured experience medical case data, an expert experience knowledge graph and a traditional Chinese medicine knowledge graph knowledge base, carrying out mixed retrieval to carry out pre-differentiation, calling multi-agent consultation according to preliminary disease differentiation and syndrome types, and obtaining an expert diagnosis scheme for risk verification and prescription adjustment optimization. According to the invention, a multi-agent collaborative diagnosis technology is utilized, and a multi-agent architecture for simulating real traditional Chinese medicine consultation is constructed. A plurality of expert agents perform independent diagnosis and complement each other, so that the limitation of a single agent is avoided, and comprehensive and accurate diagnosis is provided. And in combination with expert experience knowledge graph and big language model reasoning, the system can flexibly differentiate symptoms according to the symptoms of the patient, accurately judge disease types and syndrome types, and improve the differentiation accuracy.

The invention relates to the technical field of traditional Chinese medicinal material identification, in particular to a traditional Chinese medicinal material intelligent identification and grading system based on deep learning, which integrates image acquisition, feature extraction, expression optimization, identification evaluation and origin traceability into a whole. Curvature, structure tensor and spectral features are extracted in combination with a differential geometry theory; constructing a Riemannian manifold representation space and performing isometric embedding dimension reduction optimization; identifying the types of the medicinal materials by using a deep convolutional neural network, and comparing with a standard model to evaluate the quality grade; the origin discrimination is realized based on the multi-scale feature comparison of geodesic distance, the category, quality and traceability information of the medicinal materials are comprehensively output, the surface visual features and internal component information of the traditional Chinese medicinal materials are comprehensively utilized through a multi-source data fusion technology, and the feature expression ability and discrimination precision of the recognition system are comprehensively improved.

The invention discloses a traditional Chinese medicine physique intelligent migration identification method oriented to cross-regional crowd adaptation. According to the method, data of source region crowds are collected, feature fusion is carried out to obtain comprehensive physical feature representation, and the comprehensive physical feature representation is input into a trained physical recognition model to generate classification parameters. And extracting local feature representation by using small sample data of the target region crowd, and combining with the classification parameters to obtain initial cross-region mapping features. And performing difference decomposition on the initial mapping features, distinguishing region-independent shared features and region-related specific features, and generating cross-region adaptive features through alignment of the shared features and the source region comprehensive feature representation. And obtaining a cross-region physique identification result according to the cross-region adaptive features and the region specific features. The problem that the accuracy of an existing physique identification model in cross-region application is reduced is effectively solved, accurate adaptation under the small sample condition is achieved, and the generalization performance and the practical value of traditional Chinese medicine physique intelligent diagnosis are improved.

The invention discloses a multi-source confidence perception insomnia intelligent prescription recommendation method, a medium and equipment, and aims to solve the problem of low recommendation accuracy caused by insufficient multi-source heterogeneous data fusion, single feature representation and missing prediction confidence in the prior art. The method comprises the following steps: coding patient symptoms into a sparse binary matrix; extracting a symptom-traditional Chinese medicine prescription matrix and a symptom-symptom type matrix from the traditional Chinese medicine knowledge map; generating symptom-guided traditional Chinese medicine features and symptom type features through a double-layer graph convolutional neural network; calculating the prediction distribution probability of the traditional Chinese medicine prescriptions and syndromes; based on an energy function, quantifying uncertainty scores of the two; the multi-source probability is dynamically weighted and fused to improve the weight of a high-confidence result; and finally, outputting recommended prescriptions and syndrome type sequences. The accuracy and interpretability of insomnia prescription recommendation are remarkably improved through isomeric map modeling and multi-source confidence fusion, and the method is suitable for a traditional Chinese medicine clinical auxiliary decision making system.

The invention relates to the technical field of health assessment, in particular to a traditional Chinese medicine health assessment method and system based on intelligent analysis, and the method comprises the steps: carrying out the multispectral image collection of the face and tongue picture of a user, carrying out the color gradation quantification processing and texture feature extraction of the obtained image data, and obtaining a face color gamut feature matrix and a tongue picture texture feature vector; and based on the tongue picture-complexion associated features and a syndrome description text input by the user, performing intelligent classification pre-judgment on traditional Chinese medicine syndrome types to obtain an initial syndrome label set, and based on user physique data, correcting the initial syndrome label set to obtain a syndrome feature fusion vector. Through the health fluctuation index and the health trend early warning signal, the change of the health condition of the user can be dynamically evaluated, and a personalized health intervention scheme is generated on the basis, so that the fluctuation of the health condition can be reflected in real time, intervention measures can be taken in time, and potential health risks can be prevented.

The invention provides an acupuncture point accurate positioning device based on machine learning, and relates to the field of artificial intelligence. Comprising a multi-modal data acquisition module, a data preprocessing module, a machine learning processing module, a dynamic adaptive calibration module, a gender specificity optimization module, a laser projection module and an interaction and control module, wherein the multi-modal data acquisition module is used for acquiring human body surface sign information and human body three-dimensional space coordinate information; temperature difference information and human body posture data of the acupoint area and surrounding tissues; the machine learning processing module is internally provided with a trained improved convolutional neural network model, performs feature extraction and fusion on the data processed by the preprocessing module, and outputs initial acupuncture point coordinates; the dynamic self-adaptive calibration module dynamically corrects the coordinates of the acupuncture points; the gender specificity optimization module analyzes gender information of a patient and performs targeted adjustment on initial acupuncture point coordinates. According to the invention, the defects in precision, efficiency, adaptability and scene expansibility in the prior art are overcome.

The invention relates to the technical field of medical knowledge retrieval, in particular to a traditional Chinese medicine acupuncture field knowledge retrieval method and system based on deep learning, and the method comprises the following steps: obtaining an acupoint sequence and combining with semantics to construct a vector fragment, extracting symptom-related acupoint analysis response to generate a path sequence, and extracting a root combination vector matrix; according to the method, the sequence information of the acupuncture points in the meridian path is extracted, the semantic description and the major content are combined to construct the structured expression, the path organization and recognition capability is enhanced, the curative effect level and the treatment cycle are fused to form the sequence, the response pertinence of the acupuncture points is improved, and the method has the advantages of being simple in structure, convenient to operate and high in practicability. Through major treatment, direction and positioning root three-dimensional combination vectorization expression, semantic comparison and standardization are enhanced, keyword matching frequency and distribution density are combined, semantic association between input and knowledge is enhanced, and acupoint combinations are screened based on semantic matching and path continuity, so that the result is ensured to have relevance and practicability.

The invention relates to a traditional Chinese medicine syndrome intelligent identification method and system based on multi-modal data fusion, and belongs to the technical field of medical systems, and the method comprises the following steps: S1, multi-modal traditional Chinese medicine data acquisition: obtaining at least two different types of original data related to traditional Chinese medicine; s2, performing cleaning, denoising, normalization and data alignment processing on the various types of original data acquired in the step S1 to obtain standardized multi-modal data; s3, multi-modal data fusion is carried out, and a feature layer fusion or decision-making layer fusion mode is adopted; s4, identification model training: matching the fusion feature vector with a corresponding traditional Chinese medicine syndrome label, and inputting the matching result into a preset deep learning model for training to obtain a traditional Chinese medicine syndrome identification model; and S5, intelligently identifying the traditional Chinese medicine syndromes, and outputting a corresponding traditional Chinese medicine syndrome identification result. According to the method, full-process automatic processing and closed-loop optimization are realized, and the dependence on the professional level of operators is greatly reduced.

The invention provides a large and small model collaborative traditional Chinese medicine prescription optimization method and system, a terminal and a storage medium, and the method comprises the steps: firstly determining a prescription needing to be optimized, sorting related public literatures into an input document, constructing a local prescription knowledge base, and carrying out question answering based on a prescription optimization large language model to obtain a large model optimization prescription; then, determining related pathway targets of applicable symptoms in the prescription needing to be optimized, collecting chemical substances in the prescription needing to be optimized to obtain a prediction result of a pharmacodynamic substance level, performing medicinal material tracing analysis on the prediction result, optimizing prescription composition based on pharmacodynamic substance weight to obtain a small model optimized prescription, and determining the pharmacodynamic substance weight based on the small model optimized prescription. And performing comprehensive analysis based on the large model optimization prescription and the small model optimization prescription to generate final prescription optimization recommendation. The efficient traditional Chinese medicine prescription composition optimization method is constructed from the macroscopic level and the microscopic level, and the scientificity and the practicability of prescription optimization can be improved.

The invention provides a block chain-based traditional Chinese medicine decoction whole process credible tracing method and system, and the method comprises the steps: carrying out the structural analysis of a traditional Chinese medicine prescription, and generating a standardized prescription parameter; acquiring an image of each medicinal material, and outputting a consistency verification result sequence and a visual feature hash set based on an image recognition vector; obtaining the standardized prescription parameters and image recognition vectors, and generating a control execution sequence through a control generation model; in the medicine decocting process, actual execution data are collected, behavior consistency scoring is conducted on the actual execution data and the control execution sequence, and the consistency score and the sudden change stability index of the temperature control behavior and the control plan in the whole execution process are calculated; and packaging the indexes and the hash value of the actual execution data into a structured data block, and writing the structured data block into a block chain for evidence storage. According to the invention, a systematic technical path is provided for standardization, intellectualization and responsibility investigation of traditional Chinese medicine decoction.

The invention belongs to the technical field of traditional Chinese medicine information processing, and provides a traditional Chinese medicine disease prescription data base construction method and system.The method comprises the steps that five types of data including ancient literatures, modern medical records, prescription data, traditional Chinese medicine resources and medical record manuscript images are accessed through an extensible adapter frame; a traditional Chinese medicine term service platform is constructed by using multi-source term resources, and standardized data is generated from the analyzed data; the method comprises the following steps: extracting diseases, syndromes, prescriptions and traditional Chinese medicine entities by adopting a rule engine and a domain self-adaptive entity recognition model, on the basis of a public traditional Chinese medicine standard knowledge graph, aggregating neighbor node information through GAT, and introducing a contrast learning optimization entity relationship classifier to obtain an enhanced entity vector and classify a semantic relationship; constructing a knowledge graph based on the extracted semantic relationship; and carrying out data quality and algorithm performance monitoring and tracing on data access analysis, standardization processing, knowledge extraction and graph construction. Uniform access and standardized integration of multi-source heterogeneous traditional Chinese medicine data are realized.

The invention discloses a multi-modal traditional Chinese medicine insomnia differentiation method based on multi-task deep learning, which comprises the following steps: S1, collecting tongue images and clinical text symptoms of an insomnia patient, and respectively constructing a data set I and a data set II; s2, based on the data set I and the data set II, constructing and training a multi-mode traditional Chinese medicine insomnia differentiation model; and S3, inputting the standardized tongue picture image and the structured symptom vector of the patient into the multi-mode traditional Chinese medicine insomnia dialectical model to obtain a nine-classification result matched with the traditional Chinese medicine insomnia type. According to the method, tongue body segmentation, cross-modal representation construction, quality perception fusion and multi-task prediction can be automatically completed in actual deployment, and probability distribution of nine types of symptoms and a final conclusion are output on a symptom task.

The invention relates to the technical field of traditional Chinese medicinal material breeding, in particular to a traditional Chinese medicinal material breeding parameter regulation and control method and system based on characterization characteristics. The method comprises the steps that according to time nodes, a characterization characteristic detection unit is used for detecting traditional Chinese medicinal material plants to obtain multiple characterization characteristic sequences, and a breeding parameter detection unit is used for detecting a breeding environment to obtain multiple characterization characteristic sequences; a representation characteristic value and a breeding parameter value are calculated respectively; a parameter fitting curve is constructed based on the representation characteristic value and the breeding parameter value; a mapping relation table is constructed according to the parameter fitting curve; a target breeding parameter sequence is obtained; the method comprises the following steps: detecting a traditional Chinese medicinal material plant in a target cultivation environment to obtain a target characterization characteristic sequence, and verifying the target characterization characteristic sequence to obtain a detection result. The method can solve the problem of inaccurate parameter regulation and control in the breeding process of traditional Chinese medicinal materials at present.

The invention discloses a traditional Chinese medicine clinical auxiliary decision making system and method based on a multi-mode large language model. According to the method, through a multi-modal information perception and fusion step, visual feature extraction is carried out on a tongue picture image, and the tongue picture image is fused with clinical text semantics; through a case matching step of retrieval enhancement, similar cases are retrieved from a clinical case knowledge base; a clinical auxiliary evaluation report including syndrome discrimination, diagnosis conclusion, traditional Chinese medicine prescription and reasoning process is generated through a context-aware diagnosis generation step; and the clinical rationality of an output result can be ensured by adopting field customization indexes through specialized evaluation steps. A corresponding system comprises a tongue diagnosis generator, a clinical case knowledge base, a diagnosis generator and other components, and end-to-end clinical decision support is achieved. According to the method, the problems of difficulty in integrating multi-modal information, lack of professional data sets and the like in traditional Chinese medicine diagnosis are effectively solved, and doctors are assisted to improve the accuracy and reliability of diagnosis results.

The invention provides a traditional Chinese medicine tongue diagnosis auxiliary diagnosis system based on artificial intelligence. The traditional Chinese medicine tongue diagnosis auxiliary diagnosis system comprises a tongue picture acquisition and preprocessing module, a tongue picture feature intelligent extraction module, a traditional Chinese medicine syndrome differentiation intelligent reasoning module and a diagnosis result integration and output module which are connected in sequence. Through multi-module cooperation and algorithm fusion, the pain points of traditional tongue diagnosis and an existing intelligent system are effectively solved.

The invention discloses a fuzzy theory fused tongue diagnosis characteristic quantitative analysis method and system, and relates to the technical field of traditional Chinese medicine tongue diagnos.The method comprises the steps that a micro piezoelectric sensor array and a hyperspectral imaging module are integrated, tongue surface Young modulus distribution data and hyperspectral reflectivity data are synchronously collected, and a multi-mode tongue picture fusion data set is generated; further performing crack region segmentation and super-resolution reconstruction through a neural network model, outputting a crack network diagram and a tongue papilla form entropy, generating topological fingerprints in combination with continuous homology analysis, identifying a mechanical gradient mutation region and extracting a metabolic index, constructing a mechanical-metabolic associated feature set, and obtaining a mechanical-metabolic associated feature set; topological fingerprints and mechanical-metabolic characteristics are fused in a three-dimensional space-time coordinate system, a dynamic intuitionistic fuzzy decision field is constructed, finally, tongue picture pathology evolution risk indexes and a visual early warning report are output through a pathology prediction model, and the system provides quantifiable decision support for'prevention before illness' in traditional Chinese medicine.

The invention discloses a Chinese patent medicine prescription intelligent assistance method and system, and the method comprises the steps: determining a possible traditional Chinese medicine diagnosis range through disease information / patient information, carrying out the further analysis, obtaining the disease feature information / patient feature information which needs to be obtained for determining the traditional Chinese medicine diagnosis, and determining the traditional Chinese medicine diagnosis according to the related information. The Chinese patent medicine prescription intelligent auxiliary system comprises a demand acquisition module, a feature information analysis module, an information acquisition module and a traditional Chinese medicine diagnosis analysis module. According to the Chinese patent medicine prescription intelligent assistance method and system, doctors and patients can be helped to accurately select Chinese patent medicines, and damage caused by misuse of the medicines is prevented.

The invention discloses a traditional Chinese medicine prescription efficacy prediction system and method based on a dual-encoder Transformer, and belongs to the technical field of crossing of artificial intelligence and traditional Chinese medicine informatization. Constructing a double-layer embedding expression module comprising a drug embedding layer and a chemical component embedding layer; extracting component aggregation expression of each medicine by using a grading Transform encoder and a content gating attention mechanism; dynamically fusing the expression into the input of a drug-grade encoder through a component information injection module; a compatibility perception bias matrix is introduced into a drug-grade encoder to learn the compatibility relationship between drugs; and finally, based on prescription comprehensive representation output by a drug-grade encoder, synchronously outputting probability distribution of disease indications and targeted tissues through a multi-task prediction module. According to the method, collaborative modeling of the hierarchical structure of the traditional Chinese medicine prescription is realized, the dynamic nature of feature representation and the prediction accuracy are improved, and multi-task learning and the interpretability of a prediction result are supported.

The invention provides an intelligent symptom machine distinguishing and treating system based on four diagnostic methods of traditional Chinese medicine. The system comprises a four diagnostic method information acquisition module used for acquiring multi-modal data; the multi-modal data processing module is used for preprocessing the multi-modal data; the feature fusion module is used for carrying out feature fusion on the preprocessed data, and the domain-specific reasoning core module is used for carrying out traditional Chinese medicine pathogenesis dialectical reasoning on fused features based on a thinking chain technology and outputting structured results including dialectical analysis, syndrome types, treatment rules and prescriptions; the traditional Chinese medicine knowledge graph enhancement module is used for performing verification, constraint and knowledge enhancement on the structured result and outputting a second structured result; the interpretability output module is used for outputting a diagnosis and treatment report according to the second structured result, and displaying the diagnosis and treatment report through a graphical user interface. The application utilizes a domain-specific large language model to deeply understand complex association among symptoms and infer pathogenesis behind, and generates a complete syndrome differentiation and treatment scheme conforming to traditional Chinese medicine logic; the intelligent degree is high, and reliability guarantee is provided for clinical application through integration of the traditional Chinese medicine knowledge graph.

The invention belongs to the technical field of traditional Chinese medicine information processing, and provides a traditional Chinese medicine disease medical case database construction and management system, which comprises a data acquisition module for acquiring original traditional Chinese medicine medical case data from a plurality of heterogeneous data sources; the data processing module is used for sequentially carrying out preprocessing, standardization and deep structured processing on the original data; the knowledge graph engine module is responsible for constructing, storing and managing a traditional Chinese medicine case knowledge graph; the database storage module adopts a distributed storage architecture to store standardized medical case data and a knowledge graph; and the intelligent query and analysis module receives a request input by a user in a natural language or a structured query condition, executes multi-hop association retrieval and bidirectional path reasoning based on the traditional Chinese medicine medical case knowledge graph, and outputs medical case data meeting the condition and an association knowledge reasoning result. According to the system and the method, systematized integration and deep mining are performed on traditional Chinese medicine case data, and through cooperative work of multiple modules, the limitations of data dispersion, different formats and low retrieval efficiency in traditional medical case management are broken through.

The invention relates to the technical field of health data analysis, in particular to a traditional Chinese medicine children physique and pathology analysis system which comprises an electroencephalogram signal sensing module, a phase deviation feature extraction module, a wave band energy delay analysis module, a physique type judgment module and a pathology risk prediction module. According to the method, frequency domain analysis and phase offset calculation are carried out on electroencephalogram signals, accurate quantification of sleep state sign characteristics is achieved, the sequential relation between the phase change trend and wave band energy is captured, a dynamic characteristic combination capable of reflecting the rhythm transfer rule is constructed, the separability of physique differences is enhanced in a nonlinear mapping mode, and the accuracy of the physique differences is improved. A classification process is kept stable in a high-dimensional space, and a multi-factor prediction system is formed by combining indexes such as energy delay and phase anomaly, so that health state assessment has continuity and sensitivity, risk change can be identified in an early stage, and refined judgment of children's pathological tendency and improvement of result robustness are realized.

The invention relates to a diagnosis and treatment result prediction method fusing a time sequence and traditional Chinese medicine multi-stage diagnosis and treatment, belongs to the technical field of traditional Chinese medicine diagnosis and treatment prediction, and solves the problem of lack of accurate whole-process prediction in the prior art. The method comprises the following steps: acquiring the current doctor-seeing symptom and historical doctor-seeing time sequence data of a to-be-predicted patient; the historical treatment time sequence data comprises symptom, syndrome, therapy and prescription data of each time step; constructing a graph structure corresponding to each time step of the historical doctor-seeing time sequence data; extracting a symptom feature sequence, a syndrome feature sequence, a therapy feature sequence and a prescription feature sequence by adopting a trained graph neural network model based on the graph structure and the current treatment symptom; and based on the symptom feature sequence, the syndrome feature sequence, the therapy feature sequence and the prescription feature sequence, performing multi-stage diagnosis and treatment result prediction by adopting a trained recurrent neural network model to obtain the prediction results of the syndrome, the therapy and the prescription of the current doctor seeing of the to-be-predicted patient. And accurate whole-process prediction is realized.

An intelligent traditional Chinese medicine pulse diagnosis system based on a robot with a body relates to the technical field of intelligent traditional Chinese medicine diagnosis and comprises a mechanical arm, and a bionic finger assembly is mounted at the tail end of the mechanical arm; the bionic finger assembly comprises three independently-driven multi-degree-of-freedom bionic fingers, and a multi-modal sensing unit is arranged at the finger pulp of each bionic finger; the control unit is used for controlling the mechanical arm and the bionic finger assembly to act according to the target wrist position, and pulse feeling operation is conducted; the data acquisition unit is used for acquiring an output signal of the multi-mode sensing unit; the intelligent diagnosis unit is used for deeply analyzing the collected signals to obtain corresponding diagnosis characteristics, comprehensively analyzing the diagnosis characteristics according to a traditional Chinese medicine pulse diagnosis theoretical model and outputting diagnosis results; the system is used for solving the problems that data collection of a traditional pulse diagnosis system is limited and data analysis cannot be combined with the traditional Chinese medicine pulse diagnosis theory.

The invention relates to the technical field of image analysis, in particular to a traditional Chinese medicine acupuncture positioning method and system based on image processing, and the method comprises the following steps: collecting a posture image, analyzing the deviation and motion state of an included angle, screening a bone segment with a stable structure, mapping acupuncture point anchoring input, recognizing the sudden change of a proportion, and adjusting the coordinates of the bone segment. And after affine errors are compared, graph mapping information is obtained, and acupoint path output annotation records are segmented. According to the method, by analyzing the posture deviation and the bone chain dynamic characteristics, the judgment capacity for the motion state is enhanced, the stable structure is screened through the bone segment included angle change trend, the acupoint anchoring precision is improved, the accuracy of bone segment structure fitting is optimized by combining the proportion trend and mutation point recognition, and the accuracy of bone segment structure fitting is improved by adopting bidirectional mapping error comparison and type classification. According to the method, the adaptability of graph coordinates and template matching is improved, continuous segmentation and structure recognition of path paragraphs are achieved through sliding window merging and label labeling, acupuncture point positioning is more coherent, and the structure is clear.

The invention discloses a traditional Chinese medicine active ingredient interpretability analysis method and system based on hierarchical attention weight tracing, and belongs to the cross technical field of artificial intelligence and traditional Chinese medicine informatics. The system comprises an attention extractor, a calibrator, an importance spreading device, a compatibility analyzer and a visualization generator. Joint calibration based on entropy and gradient is carried out on the original drug-grade attention weight extracted from the dual-encoder Transform model; reversely spreading the importance predicted by the model to a drug level and a chemical component level of each drug layer by layer through a calibrated attention matrix and a hidden state semantic relationship; and finally, calculating a compatibility contribution value between any two medicines by analyzing attention paths and semantic interaction. Hierarchical explanation from drugs to chemical components is provided, the synergetic or antagonistic relationship among the drugs is quantitatively revealed, and objective evaluation is carried out through multi-dimensional indexes such as loyalty and integrity.

The invention relates to the technical field of knowledge graph reasoning, in particular to a multi-modal symptom reasoning inquiry modeling method based on a knowledge graph and a health assessment system, and aims to realize fine-grained semantic docking of symptom expression and graph entities by accurately mapping subject-called structure verbs and tongue picture semantic nodes in natural language input. The structured expression ability of the inquiry information is enhanced, the integrity of a path chain and the preciseness of inference logic are ensured by introducing sequential logic of path forbidden edge elimination, hop count statistics and connection state verification in the map path screening process, the semantic normalization of inquiry result expression and the structural definition of prompt content are improved, and the accuracy of the inquiry information is improved. The entity consistency and connection directivity in a final node connection path structure are processed through the residual network, the structure controllability in the whole process from natural language input to explainable conclusion output is enhanced, and the traditional Chinese medicine structure reasoning preciseness and output content standardization are improved.

The invention discloses a traditional Chinese medicine four diagnosis comprehensive diagnosis method and device integrated with AI analysis, and relates to the field of intelligent medical treatment, and the method comprises the steps: obtaining user identity information and basic physiological parameters at least comprising age, gender, height and weight, carrying out the correlation binding of the two, and constructing a user exclusive diagnosis file; a preset camera is combined with a color card correction mechanism to collect tongue surface, tongue bottom and face images of a user, the shooting angle and focusing parameters are automatically adjusted in the collection process, and ambient light interference is eliminated through the color card correction mechanism; according to the method, the traditional Chinese medicine syndrome element mapping matrix is converted into the syndrome score, the personalized health report containing multi-dimensional information is generated based on the analysis result, and the file is associated to support multi-mode acquisition, so that traditional Chinese medicine four-diagnosis data acquisition precision, analysis intelligence and diagnosis personalization are integrally realized, the traditional Chinese medicine four-diagnosis efficiency and accuracy are effectively improved, and the traditional Chinese medicine four-diagnosis efficiency and accuracy are improved. And comprehensive and adaptive health assessment is provided for the user.

The invention relates to the technical field of artificial intelligence and traditional Chinese medicine diagnosis, in particular to a traditional Chinese medicine tongue diagnosis image intelligent analysis system based on deep learning, which comprises a tongue picture acquisition module, a tongue picture measurement module, a tongue picture comparison module, a tongue picture comprehensive analysis module, a health consultation module and a data management module. Accurate extraction and quantitative analysis of tongue picture color features are realized by constructing a color manifold space and introducing Riemannian metric tensor and geodesic distance calculation; performing dynamic evolution tracking on tongue image change by adopting a thermal equation and a curvature flow model on a manifold; based on the geodesic distance, constructing a mapping relation between color features and syndromes, and generating syndrome probability distribution; meanwhile, tongue images collected at different times are compared and analyzed, the treatment effect is evaluated, the system is further combined with a traditional Chinese medicine knowledge graph, syndrome diagnosis, disease interpretation and dialectical treatment suggestions are provided, and the limitation that traditional tongue diagnosis is high in subjectivity and lacks quantitative standards is broken through.

The invention provides a holographic inspection information enhancement method, system and device based on DPO and RAG, and relates to the technical field of holographic inspection information enhancement, and the method comprises the steps: constructing a traditional Chinese medicine original corpus and a traditional Chinese medicine knowledge graph; generating a cold start data set from the traditional Chinese medicine original corpus through an external teacher model; on the basis of the cold start data set, performing supervised fine tuning training on the Qwen2.5 7B pre-training model to obtain a preliminary diagnosis model Model1; based on a new reasoning path generated by Model1, performing multi-dimensional quality evaluation in combination with an RAG mechanism to obtain a human preference comparison data set; performing optimization training on the Model1 through a DPO method based on a human preference comparison data set to obtain an optimization diagnosis model Model2; and carrying out backtracking correction on an output result of the Model2 in combination with an RAG mechanism. According to the scheme, the theoretical preciseness of training data is ensured through a dual data purification mechanism of sampling rejection and RAG enhancement; and a dynamically adjusted DPO algorithm is adopted to realize fine-grained alignment of traditional Chinese medicine syndrome differentiation logic.