Discussion on Modern Development of Traditional Chinese Medicine Diagnosis Based on Artificial Intelligence
10.13422/j.cnki.syfjx.20250814
- VernacularTitle:基于人工智能探讨中医诊断的现代化发展
- Author:
Kun LIAN
1
;
Xueqin WANG
1
;
Duoting TAN
1
;
Weijun LI
1
;
Lin LI
1
;
Xin LI
1
;
Zhixi HU
1
Author Information
1. Hunan University of Chinese Medicine， Changsha 410208， China
- Publication Type:Journal Article
- Keywords:
traditional Chinese medicine diagnosis;
artificial intelligence;
objectification of four diagnostic methods;
intelligent differentiation;
standardized data
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2026;32(9):336-346
- CountryChina
- Language:Chinese
-
Abstract:
Traditional Chinese medicine （TCM） diagnostics is a discipline that studies the basic theories and fundamental skills of diagnostic methods， disease diagnosis， and differentiation in accordance with the theories of TCM. The artificial intelligence （AI） technology has gained remarkable achievements in the intelligentization of the four diagnostic methods in TCM and the standardization of differentiation and diagnosis. However， it still faces many challenges. The standardization of clinical data collection is difficult， and the data quality is uneven， which affects the usability of the data. The integration of the four diagnostic information is insufficient. Most instruments can only collect data from a single diagnostic method， lacking overall integrity. The scientific nature of the diagnostic model needs to be improved. The existing models lack dynamics and the reasoning logic of TCM differentiation. The accuracy of intelligent methods needs to be improved， and the existing evaluation indicators cannot fully reflect the practical application effect of the model. Furthermore， the relevant laws and regulations are still not perfect， and data security and patient privacy lack guarantees. The cultivation of compound talents is insufficient， and there is a lack of interdisciplinary talents who are proficient in both TCM and AI. On this basis， this paper expounded on the current development status， difficulties， and bottlenecks of AI in TCM diagnosis and then explored the development trend of AI in the field of TCM diagnosis. It proposed solutions such as optimizing the data collection process， constructing multimodal diagnostic models， facilitating multi-disciplinary exchanges and cooperation， improving laws and regulations， and cultivating compound talents. It is hoped that modern， standardized， normalized， and intelligent TCM diagnosis can be further promoted， thereby providing new impetus and methods for the inheritance and innovation of TCM.
