兰州大学学报（医学版）2026，Vol.52Issue(4)：49-57,9.DOI:10.13885/j.issn.2097-681X.T20260032
中医临床辅助诊疗技术发展与展望:从大语言模型到智能体
Development and prospects of clinical decision support technologies in traditional Chinese medicine:from large language model to agents
摘要
Abstract
Traditional Chinese medicine(TCM)clinical decision support has recently shown a clear trend of technological transition.Earlier studies were mainly built on conventional deep learning frameworks,whereas current research is increasingly influenced by large language models(LLM).More recently,the emergence of agent-based methods has opened up new possibilities for interactive and collaborative diagnostic support.In this context,this review re-examined the development of TCM-oriented intelligent diagnosis and treatment,with particular attention to recent methodological changes,unresolved problems,and possible future direc-tions.On this basis,the review further turns to recent progress in medical agents.At the same time,research on TCM-specific agents is still at an early stage.Important issues,such as multi-turn closed-loop interaction,simulation of collaborative clinical workflows,and evaluation of reasoning interpretability,have not yet been adequately studied.Addressing these questions will be important for moving beyond proof-of-concept systems toward more practical and trustworthy applications.Overall,this review aimed at providing a clearer under-standing of how LLM and agents may reshape TCM clinical decision support in the coming years.关键词
大语言模型/临床辅助诊疗/医疗智能体/辨证/中医药/处方推荐Key words
large language model/clinical decision support/medical agents/syndrome differentiation/tradi-tional Chinese medicine/herbal prescription recommendation分类
医药卫生引用本文复制引用
潘格言,王瑞平,林威,周雪忠,董鑫,唐聚贤,张润顺,张磊,刘保延,郭伟,曲志成,诸强..中医临床辅助诊疗技术发展与展望:从大语言模型到智能体[J].兰州大学学报（医学版）,2026,52(4):49-57,9.基金项目
新发突发与重大传染病防控国家科技重大专项资助项目(2025ZD01903102) （2025ZD01903102）
国家自然科学基金资助项目(82374302) （82374302）
中央高校基本科研业务费专项资金资助项目(2025JBZX064) （2025JBZX064）
北京市自然科学基金资助项目(L232033) （L232033）
