688results 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 relates to the technical field of data acquisition, and discloses a laparoscopic postoperative rehabilitation data acquisition method and system based on a traditional Chinese medicine home platform. The method comprises the following steps: collecting multi-source rehabilitation data and carrying out traditional Chinese medicine syndrome differentiation analysis to obtain a rehabilitation index; inputting the rehabilitation index into an ARIMA model to predict a rehabilitation trend; discretizing the rehabilitation index to obtain a symbol, constructing a patient specificity matrix, calculating a Hamming distance to identify a rehabilitation mode, calculating an early warning index in combination with doctor intervention time, and generating a personalized rehabilitation risk assessment report. The technical problems that in existing laparoscopic postoperative rehabilitation monitoring, monitoring parameters are single, traditional Chinese medicine theoretical guidance is lacked, and rehabilitation schemes are insufficient in individuation are solved. Through multi-source rehabilitation data acquisition, traditional Chinese medicine syndrome differentiation analysis, ARIMA prediction model and patient specificity matrix construction, comprehensive monitoring, scientific prediction and personalized guidance of the rehabilitation condition of a patient are realized.

The invention relates to the technical field of artificial intelligence, and discloses a traditional Chinese medicine diabetes dry eye treatment difference evaluation system and method based on artificial intelligence, and the system comprises a four-diagnosis integrated module, a syndrome modeling module, an intelligent decision module, a curative effect feedback module, a knowledge base management module and a self-adaptive learning module. Multi-mode traditional Chinese medicine four-diagnosis data of tongue condition, pulse condition and eye diagnosis and modern physiological parameters of metabolic indexes are fused, a deep learning method is adopted for standardization processing, the problem that traditional Chinese medicine syndrome differentiation depends on subjective experience is solved, traditional Chinese medicine syndrome feature extraction of diabetes dry eye has objectivity and quantifiability, and the traditional Chinese medicine syndrome feature extraction efficiency is improved. The comprehensiveness and the accuracy of the diagnosis basis are improved; and the curative effect feedback module compares a prediction result with revival curative effect data in real time, and the knowledge base management module is linked to carry out case feature matching and strategy optimization, so that continuous optimization and long-term reliability of the treatment decision model are ensured.

The invention relates to the technical field of data processing, and discloses a data analysis method, system, terminal and medium based on a multi-modal traditional Chinese medicine large language model.The method comprises the steps that a historical tongue picture, historical voice information and historical text information of a target historical user are obtained, feature extraction is carried out, and the historical tongue picture, the historical voice information and the historical text information are obtained; obtaining a tongue picture feature vector, a sound feature vector and a syndrome feature vector; according to the tongue picture feature vector, the sound feature vector and the syndrome feature vector, performing model training on a created multi-modal big language training model to obtain a multi-modal traditional Chinese medicine big language model; and obtaining a to-be-analyzed tongue picture, to-be-analyzed voice information and to-be-analyzed text information of the target user, inputting the to-be-analyzed tongue picture, the to-be-analyzed voice information and the to-be-analyzed text information into the multi-modal traditional Chinese medicine large language model, and outputting a According to the invention, through collaborative fusion and analysis of a plurality of data modes such as tongue pictures, sound and inquiry, data analysis of a traditional Chinese medicine level can be carried out on related data of a user more comprehensively.

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 belongs to the technical field of traditional Chinese medicines, and particularly relates to a traditional Chinese medicine prescription efficacy quantification method and system.The method comprises the steps that chemical component spectrums, pharmacodynamic substance contents and biological activity indexes of traditional Chinese medicines forming a prescription are obtained; constructing a multi-target regulation and control network by combining a traditional Chinese medicine-target interaction database according to the chemical component spectrum, the pharmacodynamic substance content and the biological activity index, identifying a core efficacy pathway cluster by adopting a Louvain algorithm, and calculating a pathway activation intensity value by adopting a pathway target membership weighting model; according to the core efficacy pathway cluster, establishing a mapping relation between the core efficacy pathway cluster and traditional Chinese medicine efficacy terms through ontology and semantic mapping, and according to pathway activation intensity values, generating a prescription efficacy intensity vector through a weighted aggregation model; according to the efficacy intensity vector of the prescription, verifying and correcting the network weight through an in-vitro cell model, and generating the efficacy quantification of the prescription in combination with the clinical syndrome calibration coefficient. Therefore, the problems of single data dimension and insufficient quantification result accuracy in the prior art are solved.

The invention relates to the technical field of massage, in particular to an intelligent abdominal acupoint massage system and method based on multi-modal sensing, and the system comprises a multi-modal sensing module which comprises a 3D depth camera, an infrared thermal imager, a myoelectricity sensor and a millimeter wave radar; the intelligent decision-making module is used for updating a massage strategy in real time by applying a Poisson reconstruction algorithm, a multi-modal fusion positioning algorithm and a dynamic coordinate mapping method; the execution device comprises an end effector and is composed of a bionic massage head for executing massage, a six-dimensional force sensor for feeding back a pressure value in real time and an infrared temperature control module; the three-degree-of-freedom mechanical arm is composed of xyz translation compensation and a rotating joint and is used for controlling the end effector to move; the power module is used for supplying power to the system. The device has the advantages that accurate acupoint tracking and positioning can be provided for a user, safe, controllable, autonomously adjustable massage force is provided, and different massage schemes are set according to individuation of the physique of the user.

The invention relates to a construction method of a metabolic syndrome phlegm syndrome lipid metabolism characteristic diagnosis model. The construction method comprises the following steps: S1, acquiring a serum sample; s2, carrying out lipid metabolite analysis through a full-quantitative lipidomics formula; s3, carrying out primary screening on differential metabolites; s4, optimizing the characteristic indexes by using a random forest algorithm and stepwise regression; and S5, constructing a differential metabolite diagnosis model through Logistic regression analysis. By analyzing differential lipid metabolites of patients with MetS phlegm syndromes and non-phlegm syndromes, the invention reveals that abnormal accumulation of lipid and lipid metabolites may be the core pathological parenchyma of MetS phlegm syndromes. By integrating lipid metabonomics data, using a random forest algorithm, stepwise regression and other methods to screen feature difference lipid metabolites and construct a MetS phlegm syndrome specific diagnosis model, a novel combined biomarker and evidence-based basis are provided for early diagnosis of MetS phlegm syndromes, and a scientific basis can also be provided for objective diagnosis of traditional Chinese medicine phlegm syndromes.

The invention provides a large-model-driven traditional Chinese medicine curative effect multi-dimensional intelligent evaluation system and device, and relates to the technical field of traditional Chinese medicine curative effect intelligent evaluation. The system mainly comprises a data layer, a knowledge layer, a model layer and an application layer which are arranged in sequence; the data layer is used for collecting tongue images, pulse condition data, cardiovascular data, structured data, unstructured data and the like, and carrying out data treatment operations such as structured transformation, block chain evidence storage and abnormal value correction; the knowledge layer comprises a traditional Chinese medicine diagnosis and treatment knowledge map, a traditional Chinese medicine prescription compatibility relationship library, a curative effect evaluation standard library, a component-target network, a semantic mapping engine and a syndrome-treatment association map; the model layer comprises a multi-modal feature extraction module and a curative effect prediction module; the application layer comprises a doctor end and a patient end. According to the scheme, quantitative analysis of traditional Chinese medicine syndrome differentiation rules is realized through a large model, and the syndrome classification consistency of patients is improved.

The invention relates to the technical field of wisdom medical treatment, in particular to a cooperative intervention system and method based on multi-modal emotion perception and five-tone therapy, and realizes precision of emotion recognition and individuation of intervention strategies through cooperative intervention of multi-modal emotion perception and traditional Chinese medicine five-tone therapy. Physiological and behavior signals of a user in different states are comprehensively captured, emotion recognition is carried out in combination with a deep learning model, the accuracy and real-time performance of emotion recognition are remarkably improved, the system can intelligently match music tracks most suitable for the current emotion state based on the five-internal-organ-five-sound theory of traditional Chinese medicine and modern music psychology, and the user experience is improved. And an intervention strategy is continuously optimized through reinforcement learning, so that more targeted and effective emotion regulation is realized, and the method is particularly suitable for long-term management and intervention of negative emotions such as anxiety and depression.

The invention discloses an automatic traditional Chinese medicine decoction method based on multi-modal data analysis, a medium and equipment, and the method comprises the steps: firstly, matching a first initial decoction strategy according to traditional Chinese medicine prescription information, and generating a second initial decoction strategy in combination with individual feature data of a patient; in the decocting process, multi-mode state data such as temperature time sequence data, visual characteristic data and volatile gas component characteristic spectrum of liquid medicine in the pot body are synchronously collected; the multi-modal data and the individual influence factors are input into a dynamic optimization decision model, and the model generates a decoction strategy adjustment instruction by calculating the deviation between a real-time component spectrum and an expected trajectory and comprehensively judging safety states such as boiling intensity and dry burning risk; by dynamically adjusting the operation parameters of the decoction equipment, the composition change of the liquid medicine approaches to the optimization target, and meanwhile, the safety of the decoction process is ensured. The problems that a traditional decoction method depends on artificial experience, the quality stability is poor, and personalized precise regulation and control are lacked are solved.

The invention discloses a traditional Chinese medicine diagnosis and treatment aided decision-making method and system, and relates to the technical field of traditional Chinese medicine intelligent diagnosis and treatment aided decision-making, and the method comprises the steps: carrying out the wavelet transformation analysis of pulse condition waveform time series data, extracting a pulse condition dynamic change feature sequence, inputting a tongue image color change rate and a pulse condition feature change rate into a space-time convolution network, and obtaining a time-space convolution network; generating a tongue pulse dynamic association index and outputting a preliminary syndrome classification; fourier transform analysis is carried out on the spleen channel acupoint impedance spectrum, false-true state judgment is carried out in combination with tongue pulse dynamic correlation indexes, preliminary syndrome classification is corrected, and a false-true state quantification result and corrected syndrome classification are output; and matching the corrected syndrome classification with the traditional Chinese medicine knowledge map, adjusting the dosage according to a virtual-real state quantification result, reversely verifying the drug-syndrome specificity through a curative effect database, screening an optimal treatment scheme, and outputting a personalized diagnosis and treatment scheme. According to the method, the syndrome classification precision is improved, and an objective basis is provided for personalized dose adjustment.

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 discloses an intelligent office table self-adaptive control method and system based on artificial intelligence. The method comprises the following steps: S1, multi-modal data acquisition; s2, data preprocessing; s3, feature extraction; s4, data fusion and state identification; and S5, executing an intervention strategy. Three types of data including visual information, physiological signals and pressure distribution are fused to perform multi-dimensional state sensing of multi-modal data fusion, sitting posture key points are extracted based on a convolutional neural network (CNN), real-time recognition of bad sitting postures is realized, time sequence characteristics of pressure distribution are analyzed through a long-short-term memory network (LSTM), behavior modes such as sedentariness and heeling are recognized, and the sitting posture recognition accuracy is improved. According to the method, the association between operation habits and fatigue is mined, HRV frequency domain features are extracted by using Fourier transform, and the fatigue state is comprehensively evaluated in combination with multiple indexes, so that three-dimensional description of different states of different users is realized, and whether the users are fatigued or not is judged to provide more refined health management.

The invention discloses a traditional Chinese medicine adverse reaction risk prediction method based on a heterogeneous graph neural network, and the method comprises the following steps: obtaining data, obtaining a traditional Chinese medicine-target relation file from an ETCM database, and obtaining an adverse reaction-target relation file from an ADReCS database; data preprocessing: performing data cleaning on the obtained relation file to obtain a preprocessed file; constructing an isomeric graph, taking the traditional Chinese medicine herb, the target spot and the adverse reaction adverse as three types of nodes, and constructing the isomeric graph by utilizing the pre-processing file; node features are initialized, initial feature vectors are constructed for each type of nodes herb, target and adverse, and initial embedding of all the nodes is mapped to the same dimension space; carrying out HAPM feature fusion, inputting the node features into an HAPM heterogeneous graph attention network to carry out message passing and aggregation, and outputting a representation vector of a node level; predicting and outputting; and performing verification and feedback iteration. The invention further provides a system adopting the method. The method and the system can accurately predict the adverse reaction risk of the traditional Chinese medicine.

The invention relates to the technical field of information processing, in particular to a medicine conflict automatic detection and prescription optimization system for old multi-disease patients. According to the system, a data management module is used for collecting individual data of patients and group data of co-diseased reference groups and receiving a planned medication scheme; the parameter calculation module is used for identifying a target medicine combination with time overlapping in the patient medication record and the planned medication scheme; determining a basic risk index according to the group medication response data, the patient medication record and the work and rest text data; determining a lag risk coefficient according to the physiological indexes and the drug metabolism data; determining group medication associated risk parameters according to atypical reactions and group medication records in the medication reaction data; the risk fusion module is used for determining a drug use conflict risk value based on the basic risk index, the lagging risk coefficient and the group drug use associated risk parameter; and the prescription optimization module is used for generating an optimal medication scheme, so that the generated optimal scheme is more suitable for the actual life of the patient.

The invention discloses a traditional Chinese medicine intelligent diagnosis method and system based on a CoT large model. The method and system can be applied to intelligent health consultation service, primary medical auxiliary diagnosis, traditional Chinese medicine education training, traditional Chinese medicine knowledge popularization, remote medical support, traditional Chinese medicine scientific research assistance, health management platforms and other scenes. According to the traditional Chinese medicine intelligent diagnosis method and system based on the CoT large model, the CoT instruction is adopted to guide the large model to carry out information perfection degree evaluation on the context information, when the context information is incomplete, a guiding type question is generated to guide a user to supplement missing information, the missing information serves as supplementary input of large model reasoning, and therefore the accuracy of diagnosis is improved. The large model can obtain complete inquiry information, and then a professional, accurate and interpretable diagnosis result is generated according to the complete inquiry information. Compared with the prior art, the method has the capability of actively guiding the user to provide complete question information, and the CoT instruction is adopted to guide the large model to perform reasoning, so that the traditional Chinese medicine diagnosis capability of the large model is improved.

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 discloses a traditional Chinese medicine chronic disease dialectical treatment optimization method based on a graph neural network, and the method comprises the following steps: S1, collecting electronic medical record text data and traditional Chinese medicine knowledge data of a patient, and constructing an initial dialectical graph; s2, obtaining an initial feature vector of a node; s3, performing multi-order spiral perception processing by using a boa convolution unit, constructing a spiral adjacent path for each target node according to a structure depth and a relation direction, and introducing a structure position coding mode to perform sequential perception modeling on a node neighborhood relation to generate an adjacent feature matrix; s4, constructing a syndrome semantic tension matrix; s5, inputting the adjacency feature matrix and the syndrome semantic tension matrix into a GATv2 model to obtain a final node feature vector; and S6, outputting a syndrome type prediction result corresponding to the patient by using the final feature vector of the node, and generating prescription and drug path recommendation. According to the method, the GATv2 model and the boa convolution unit of structure perception are combined, so that traditional Chinese medicine chronic disease dialectical reasoning and drug recommendation are realized.

The invention discloses a method, a device, equipment, a medium and a product for evaluating the effect of traditional Chinese medicine on diseases, and relates to the technical field of pharmacology of traditional Chinese medicine, the method comprises the following steps: acquiring a disease data set and a traditional Chinese medicine data set of a target disease; extracting a disease target entity from the disease data set by adopting a large language model, and extracting a medicinal material entity from the traditional Chinese medicine data set; constructing a disease gene network according to each disease target entity and a Barabas PPI network; constructing a medicinal material gene network according to the target traditional Chinese medicine formula, the medicinal material entities and a Barabas PPI network; the similarity between the disease gene network and the medicinal material gene network is calculated, the similarity is used for representing the effect of the target traditional Chinese medicine formula on the target disease, and quantitative evaluation of the effect of the traditional Chinese medicine on the disease can be achieved.

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 provides an intelligent inquiry method and system based on a large language model, and the method comprises the steps: carrying out ancient book transcription, semantic logic verification and multi-stage nested JSON formatting, constructing a data set to cover core modules of diseases, herbal medicines, prescriptions, incompatibility and the like, and marking the details of dosage, processing method and the like; the method comprises the following steps: carrying out logic chain analysis on traditional Chinese medicine classical literatures based on a large model, generating independent knowledge units by adopting a dynamic semantic partitioning strategy, fusing a traditional Chinese medicine term weight matrix and drug attribute constraint optimization into confusion distillation by improving a confusion distillation technology, carrying out efficient neighbor search by utilizing FAISS, and returning a Top-K related result; and based on the knowledge fine-tuning large model, combining the retrieved context to generate safety response content conforming to the theory of traditional Chinese medicine. Based on the technical scheme, the accuracy and semantic understanding ability of a retrieval model in the field of traditional Chinese medicine are remarkably improved; the professionality and the safety of the generated model are enhanced; the accuracy and the safety are improved; the knowledge retrieval integrity is optimized through dynamic semantic partitioning.

The invention relates to the technical field of traditional Chinese medicine nursing or health improvement, in particular to a method for generating a traditional Chinese medicine personalized nursing scheme for preventive treatment of diseases. The method comprises the following steps: firstly, screening out all initial reference individuals of a current individual based on a similar condition between corresponding physique information of the individuals; further determining all concerned symptoms and corresponding concerned coefficients of the current individual according to the universality and change condition of each symptom of the current individual in the initial reference individual; screening out all reference individuals according to the attention coefficient of the common attention symptom of the current individual and each initial reference individual; and finally, generating a personalized nursing scheme of the current individual based on the nursing schemes of all the reference individuals. According to the method and the device, the reference individuals capable of providing similar nursing references are accurately screened out from the historical disease prevention individuals based on the similar physical conditions of the individuals and the similar conditions of the symptoms which are mainly concerned during nursing, so that the generation effect of the personalized scheme of the current individual is improved.

The invention relates to the technical field of intelligent detection, in particular to an intelligent detection system and method for traditional Chinese medicine purification components, and the system comprises a component extraction module, a concentration distribution correction module, a dynamic matching optimization module, a fluctuation suppression control module and an execution path adaptation module. According to the invention, through intelligent analysis and optimization of concentration distribution, temperature and pressure factors in a traditional Chinese medicine purification process, accurate control of target component concentration and impurity distribution is realized, concentration gradient data is extracted, a related model is established, change of component extraction and concentration distribution is effectively corrected, accurate separation of target components and impurities is ensured, and the purity of the traditional Chinese medicine is improved. Aiming at the fluctuation influence, the fluctuation influence in the purification process is reduced and the purification efficiency and stability are improved through dynamic optimization and adjustment of the distribution sequence and the fluctuation suppression strategy, so that the purification quality of the target component is continuously optimized, and accurate component control and high-quality purification results in the traditional Chinese medicine purification process are ensured.