Large-Scale Language Models(LLMs)have initiated transformative changes in Traditional Chinese Medicine(TCM),yet existing LLM-based diagnostic approaches face challenges such as prolonged training cycles and high imple...Large-Scale Language Models(LLMs)have initiated transformative changes in Traditional Chinese Medicine(TCM),yet existing LLM-based diagnostic approaches face challenges such as prolonged training cycles and high implementation costs due to reliance on medical expertise.To address this,we propose a systematic framework integrating multimodal data and LLM technologies.First,we analyze bottlenecks in traditional diagnosis(e.g.,subjectivity)and modernization challenges.The framework leverages open-s ource foundation models(e.g.,Baichuan2,LLaMA)pre-trained on"symptom-syndrome-medication"associations,fine-tuned with clinical data to simulate diagnostic workflows.Key components include:(1)a Data Input Layer capturing tongue image features(via YOLOv5s6/U-Net),speech spectra,BERT-encoded inquiry texts,and pulse waveforms;(2)a Feature Fusion Layer constructing syndrome differentiation vectors through multimodal feature concatenation;and(3)a Prediction&Feedback Layer generating diagnostic probabilities with reinforcement learning based on clinical efficacy.Finally,we discuss critical issues,including risks of physician replacement,professional competence degradation,and liability attr ibution in diagnostic errors.This framework aims t o enhance TCM diagnostic efficiency while ensuring clinical reliability.展开更多
Chinese medicine(CM)has thousands of years of experience in prevention of diseases.As for CM,people's constitution is closely related to their health status,thus recognition of CM constitution is the fundamental a...Chinese medicine(CM)has thousands of years of experience in prevention of diseases.As for CM,people's constitution is closely related to their health status,thus recognition of CM constitution is the fundamental and core contentof research on constitution types.With development of technologies such as sensors,arificial intelligence and big data,objectification of the four diagnostic methods of CM has gradually matured,bringing changes in the mindset and innovations in technical means for recognition of CM constitution.This paper presents a systematic review of the latest research trends in constitution recognition based on objectification of diagnostic methods in CM.展开更多
Goals of traditional Chinese medicine(TCM)include precision,accuracy,and recognition by clinical practice.Establishment of a diagnosis and treatment system that closely conforms to the principle-method-recipe-medicine...Goals of traditional Chinese medicine(TCM)include precision,accuracy,and recognition by clinical practice.Establishment of a diagnosis and treatment system that closely conforms to the principle-method-recipe-medicines system and derivation of an accurate diagnosis and treatment plan should be considerations of TCM.Artificial intelligence research based on computer technology is one of the effective ways to solve this problem.In the research of intelligent diagnosis path,reflecting the characteristics of the overall view and dialectical treatment of TCM such as"Combination of four diagnostic methods""overall examination""combination of disease and syndrome"and"treatment individualized to patient,season and locality"are key for successful research of artificial intelligence in TCM diagnosis or recognition by clinical practice.展开更多
文摘Large-Scale Language Models(LLMs)have initiated transformative changes in Traditional Chinese Medicine(TCM),yet existing LLM-based diagnostic approaches face challenges such as prolonged training cycles and high implementation costs due to reliance on medical expertise.To address this,we propose a systematic framework integrating multimodal data and LLM technologies.First,we analyze bottlenecks in traditional diagnosis(e.g.,subjectivity)and modernization challenges.The framework leverages open-s ource foundation models(e.g.,Baichuan2,LLaMA)pre-trained on"symptom-syndrome-medication"associations,fine-tuned with clinical data to simulate diagnostic workflows.Key components include:(1)a Data Input Layer capturing tongue image features(via YOLOv5s6/U-Net),speech spectra,BERT-encoded inquiry texts,and pulse waveforms;(2)a Feature Fusion Layer constructing syndrome differentiation vectors through multimodal feature concatenation;and(3)a Prediction&Feedback Layer generating diagnostic probabilities with reinforcement learning based on clinical efficacy.Finally,we discuss critical issues,including risks of physician replacement,professional competence degradation,and liability attr ibution in diagnostic errors.This framework aims t o enhance TCM diagnostic efficiency while ensuring clinical reliability.
基金Supported by Hebei Province Key Research and Development Project(No.203777119D)。
文摘Chinese medicine(CM)has thousands of years of experience in prevention of diseases.As for CM,people's constitution is closely related to their health status,thus recognition of CM constitution is the fundamental and core contentof research on constitution types.With development of technologies such as sensors,arificial intelligence and big data,objectification of the four diagnostic methods of CM has gradually matured,bringing changes in the mindset and innovations in technical means for recognition of CM constitution.This paper presents a systematic review of the latest research trends in constitution recognition based on objectification of diagnostic methods in CM.
基金the funding support from the Open Fund Project of State Key Subjects of Chinese Medicine Diagnostics,Hunan University of Chinese Medicine(No.2015ZYZD01).
文摘Goals of traditional Chinese medicine(TCM)include precision,accuracy,and recognition by clinical practice.Establishment of a diagnosis and treatment system that closely conforms to the principle-method-recipe-medicines system and derivation of an accurate diagnosis and treatment plan should be considerations of TCM.Artificial intelligence research based on computer technology is one of the effective ways to solve this problem.In the research of intelligent diagnosis path,reflecting the characteristics of the overall view and dialectical treatment of TCM such as"Combination of four diagnostic methods""overall examination""combination of disease and syndrome"and"treatment individualized to patient,season and locality"are key for successful research of artificial intelligence in TCM diagnosis or recognition by clinical practice.
