集成技术2026，Vol.15Issue(5)：83-101,19.DOI:10.12146/j.issn.2095-3135.20260517001
人工智能驱动的中医药现代化:从经验范式到数据智能范式的转变
Artificial Intelligence-Driven Modernization of Traditional Chinese Medicine:A Shift from an Experience-Based Paradigm to a Data-Intelligence Paradigm
摘要
Abstract
This paper systematically reviews the pivotal role of artificial intelligence(AI)in driving the modernization of traditional Chinese medicine,using the transition from an experience-based paradigm to a data-intelligent paradigm as the central thread.This transition should not be viewed as a simple replacement of traditional experience,but as a process through which experiential knowledge is structured,complex relationships become computationally tractable,and research conclusions become more verifiable.Focusing on 4 key domains-material basis and mechanism elucidation,intelligent prescription optimization,pharmaceutical engineering and industrial transformation,and knowledge engineering with large language models—this study analyzes how AI reshapes traditional Chinese medicine research paradigms through data-driven modeling,multimodal integration,and system-level reasoning.The findings indicate that AI is accelerating the transition of traditional Chinese medicine from experience-driven practice toward data-driven,evidence-constrained,and human-in-the-loop decision support,improving quantification and interpretability in mechanism analysis,prescription design,and quality control.However,the maturity of AI applications varies across different domains,and challenges remain in model interpretability,knowledge standardization,and ethical governance.Future research should focus on developing multimodal and multi-scale integrated intelligent models,as well as establishing a coordinated framework that aligns technological advancement with ethical considerations,in order to improve the reliability and verifiability of AI-enabled traditional Chinese medicine research.关键词
中医药/人工智能/数据驱动范式/多模态学习/系统生物学/智能配伍设计/数字孪生/知识图谱/大语言模型/伦理治理Key words
traditional Chinese medicine/artificial intelligence/data-driven paradigm/multimodal learning/systems biology/intelligent prescription design/digital twin/knowledge graph/large language models/ethical governance分类
医药卫生引用本文复制引用
贺宇翔,唐若凝,冯志炜,成文翔,柯丽青,尤志峰,李健,张鹏..人工智能驱动的中医药现代化:从经验范式到数据智能范式的转变[J].集成技术,2026,15(5):83-101,19.基金项目
广东省教育厅重点领域专项项目(2025ZDZX2064) （2025ZDZX2064）
广东省自然科学基金面上项目(2026A1515012093) This work is supported by Guangdong Provincial Department of Education Key Area Special Project(2025ZDZX2064)and Guangdong Provincial Natural Science Foundation General Program(2026A1515012093) （2026A1515012093）
