The Research Progress and Development Strategies of Traditional Chinese Medicine Diagnosis Empowered by Artificial Intelligence
10.13288/j.11-2166/r.2025.14.001
- VernacularTitle:人工智能赋能下中医诊断学的研究进展及发展对策
- Author:
Wenjun ZHU
1
;
Manshi TANG
1
;
Kaijie SHE
1
;
Zihao TANG
1
;
Minyi HUANG
1
;
Naijun YUAN
1
;
Qingyu MA
1
;
Jiaxu CHEN
1
Author Information
1. School of Traditional Chinese Medicine，Jinan University，Guangzhou，510632
- Publication Type:Journal Article
- Keywords:
artificial intelligence;
traditional Chinese medicine diagnosis;
multimodal data integration
- From:
Journal of Traditional Chinese Medicine
2025;66(14):1413-1418
- CountryChina
- Language:Chinese
-
Abstract:
The rapid development of artificial intelligence （AI） technology provides new opportunities for the modernisation of traditional Chinese medicine （TCM） diagnosis. By analysing the foundation， research progress and difficulties of the combination of AI and TCM diagnosis， it is concluded that AI has made remarkable development in intelligence-driven modernization of TCM tongue diagnosis， pulse diagnosis， listening and smelling diagnosis and text processing， and there are useful explorations in the field of constructing data-driven TCM diagnostic model and multidisciplinary integration of TCM diagnostic models. However， the current integration of AI technology in TCM diagnosis still faces many challenges， such as the scarcity and uneven quality of clinical data， the limited ability of AI algorithms to express TCM thinking model of syndrome differentiation and empirical knowledge， and the possible existence of ethical and privacy issues. By systematically sorting out the current research status and development direction of AI-empowered TCM diagnostics， it is proposed to promote the application of AI technology in TCM diagnostics in four aspects， namely， strengthening the construction of TCM big data and talent cultivation， encouraging cross-disciplinary cooperation， improving the legal and ethical framework， and promoting the popularity of the technology in primary care， so as to enhance the modernisation of TCM diagnostics.
