Large Language Models in Chinese Medicine:Potential Limitations
- VernacularTitle:大语言模型对话中医及其潜在的局限性
- Author:
Hua LI
1
;
Yuman WANG
;
Xiaoyu LIU
;
Runxue SUN
;
Shaopo WANG
;
Qian YANG
;
Yanru DU
Author Information
- Publication Type:Journal Article
- Keywords: Large language models; Traditional Chinese medicine; Patient experience; Scheduled workflow; Challenges
- From: World Science and Technology-Modernization of Traditional Chinese Medicine 2025;27(10):3031-3039
- CountryChina
- Language:Chinese
- Abstract: The emergence of generative pre-training transformer(GPT)and large language models(LLMs)has brought transformative applications to the medical field.In traditional Chinese medicine,LLMs offer unique opportunities to address in efficiencies in clinical workflows and improve the patient experience.However,the seprospects have challenges,including data quality,security and privacy,disinformation,ethics,and other issues.This paper systematically elaborates on the application of Large Language Models(LLMs)in Traditional Chinese Medicine(TCM),highlighting their value in improving TCM services,enhancing teaching effectiveness,and optimizing healthcare management processes,while conducting an in-depth analysis of potential technical and ethical challenges during real-world implementation.Preventive measures are necessary to ensure the safe and unbiased use of large language models in TCM clinical practice.We encourage clinicians and researchers to address current challenges and optimize largelanguage models while reducing associated risks.The deployment and implementation of large language models in TCM clinical practice will significantly contribute to the dissemination and development of TCM culture.
