Strategies for Building an Artificial Intelligence-Empowered Trusted Federated Evidence-Based Analysis Platform for Spleen-Stomach Diseases in Traditional Chinese Medicine
10.13288/j.11-2166/r.2026.01.015
- VernacularTitle:人工智能赋能中医药脾胃病可信联合循证分析平台构建策略
- Author:
Bin WANG
1
;
Huiying ZHUANG
1
;
Zhitao MAN
1
;
Lifeng REN
2
;
Chang HE
1
;
Chen WU
2
;
Xulei HU
2
;
Xiaoxiao WEN
3
;
Chenggong XIE
1
;
Xudong TANG
4
Author Information
1. Institute of Information on Traditional Chinese Medicine，China Academy of Chinese Medical Sciences，Beijing，100700
2. BOYA Regulation and Compliance Blockchain Technology Co.，Ltd
3. Traditional Chinese Medicine Science and Technology Cooperation Center，China Academy of Chinese Medical Sciences
4. Institute of Gastroenterology，Xiyuan Hospital，China Academy of Chinese Medical Sciences
- Publication Type:Journal Article
- Keywords:
spleen-stomach diseases;
artificial intelligence;
traditional Chinese medicine data;
trusted federated evidence-based analysis platform
- From:
Journal of Traditional Chinese Medicine
2026;67(1):95-102
- CountryChina
- Language:Chinese
-
Abstract:
This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.
