中医药古籍数智化的研究进展与应用前景

doi:10.3969/j.issn.1001-8131.2026.01.038

Abstract
Figure/Table
References
Related Citation (2)

Download: PDF (823 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Ancient Chinese medical texts serve as the core carriers for the inheritance and innovation of traditional Chinese medicine(TCM)scholarship.The digitalization of these texts offers a novel pathway for their utilization,preservation,and dissemination.Given the challenges TCM ancient texts face—such as obscure knowledge,disconnection between ancient and modern contexts,and incomplete mechanisms for application and transformation—there is an urgent need to leverage artificial intelligence and big data technologies to overcome technical and practical hurdles.This paper systematically reviews research advancements in the digitalization of TCM ancient texts across data organization,technological applications,platform development,and clinical empowerment.It also outlines future directions,including precise clinical decision-making support,the intelligent inheritance of renowned physicians' expertise,auxiliary drug development,and multidisciplinary integration.The goal is to elevate TCM ancient texts from "support tools"to"decision-making partners," providing theoretical foundations and practical references for the intelligent inheritance and innovative development of TCM.

Key words： ancient books of traditional Chinese medicine artificial intelligence Large Language Model(LLM) Digitization of Ancient Books

Received: 03 February 2026

PACS:

R2-5

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zhang Jingyi
	Li Xiao
	Huang Xiaoying
	Zhu Qi
	Lu Tianqian

Cite this article:

Zhang Jingyi,Li Xiao,Huang Xiaoying, et al. Research Progress and Application Prospects of Digitalization in Traditional Chinese Medicine Ancient Texts[J]. journal1, 2026, 46(1): 131-135.

URL:

http://www.hrbyybjb.org.cn/EN/10.3969/j.issn.1001-8131.2026.01.038 OR http://www.hrbyybjb.org.cn/EN/Y2026/V46/I1/131

[1] 国务院办公厅关于印发“十四五”中医药发展规划的通知[J].中华人民共和国国务院公报,2022,(11):8-21.
[2] 李欣桐,马素芬,张丰聪,等.中医药领域大语言模型的研究进展与应用前景[J].南京中医药大学学报,2024,40(12):1393-1403.DOI:10.14148/j.issn.1672-0482.2024.1393.
[3] 杨涛,王欣宇,朱垚,等.大语言模型驱动的中医智能诊疗研究思路与方法[J].南京中医药大学学报,2023,39(10):967-971.DOI:10.14148/j.issn.1672-0482.2023.0967
[4] 宋逸杰,马素亚,戴亚盛,等.人工智能辅助中医辨证的关键问题与技术挑战[J].中国工程科学,2024,26(2):234-244.
[5] 佟琳,柴忠言,李兵,等.中医药典籍知识融合推理大模型构建与应用研究[J].中国中医基础医学杂志,2025,31(12):2130-2134.
[6] 李兵,佟琳,张华敏.中医典籍数智化应用发展路径与展望[J].中国中医基础医学杂志,2025,31(12):2078-2081.
[7] 贾李蓉,刘静,于彤,等.中医药语义网络顶层框架研究[J].中国中医药信息杂志,2021,28(5):1-6.
[8] 周树斌,周宇婷,施州州,等.基于可视化和内容分析的我国中医古籍数智化研究现状与展望[J].图书情报研究,2020,13(4):101-108.
[9] 胡谦锋,杨心怡,高雨,等.国内中医古籍数智化研究现状及发展趋势分析[J].中国中医药图书情报杂志,2024,48(6):1-6.
[10] 王凤兰. 基于知识元的中医古籍文献研究述评[J].南京中医药大学学报,2022,38(12):1170-1174.
[11] 陈健,杨凤,任巧生,等.基于知识元理论的中风病古籍医案知识表示与古今双模知识图谱构建研究[J].中国中医药信息杂志,2024,31(11):24-32.
[12] 张晓晓. 《金匮要略》知识图谱构建及应用研究[D].北京:北京中医药大学,2022.
[13] 李连新,杨璠,朱兆鑫,等.中医人工智能辨证研究现状与发展[J].世界科学技术-中医药现代化,2021,23(11):4268-4276.
[14] 任玉兰,李政,梁红,等.中医古籍数智化建设与知识服务模式的构建[J].世界科学技术-中医药现代化,2013,15(1):45-48.
[15] 杨继红. 中医古籍数智化资源建设概述[J].现代情报,2008,28(5):136-138.
[16] 李贺,刘嘉宇,祝琳琳,等.中医古籍数智化平台服务质量评价与提升策略研究[J].现代情报,2023,43(11):58-72.
[17] 熊枫,宋国强.高校中医古籍数字资源建设现状调查研究[J].内蒙古科技与经济,2020,15(4):97-99.
[18] 曹霞,裴丽.中医古籍数智化建设实践分析与应对策略[J].图书馆学研究,2016,13(7):42-44.
[19] 潘晔,娄静,潘玉颖,等.中医药数据挖掘现状分析与创新探索[J].中国中医药信息杂志,2022,29(5):5-9.
[20] 张君冬,杨松桦,刘江峰,等.AIGC赋能中医古籍活化:Huang-Di大模型的构建[J].图书馆论坛,2024,44(10):103-112.
[21] 阮彤,卞俣昂,余广涯,等.医学大语言模型研究与应用综述[J].中国卫生信息管理杂志,2023,20(6):853-861.