An AI-Driven Research Pathway for Upholding Fundamental Principles and Breaking New Ground of Traditional Chinese Medicine Under the Guidance of Complexity Science
10.13288/j.11-2166/r.2026.11.001
- VernacularTitle:复杂性科学思想指导下人工智能驱动中医药守正创新的研究路径探讨
- Author:
Lijiang REN
1
;
Longfei LI
2
;
Jinkai CHEN
3
;
Qingyong HE
1
Author Information
1. Guang'anmen Hospital，China Academy of Chinese Medical Sciences，Beijing，100053
2. Tsinghua University
3. School of Intelligent Science and Technology，University of Science and Technology Beijing
- Publication Type:Journal Article
- Keywords:
complexity science;
open complex giant systems;
traditional Chinese medicine;
artificial intelligence
- From:
Journal of Traditional Chinese Medicine
2026;67(11):1137-1141
- CountryChina
- Language:Chinese
-
Abstract:
Complexity science and traditional Chinese medicine （TCM） share a profound intrinsic compatibility. To address the limitations of reductionist approaches in guiding the dynamically holistic theory and practice of TCM， this paper develops a novel research pathway under the guidance of complexity science， using the open complex giant systems （OCGS） theory as its practical framework， upholding the fundamental principles of TCM and breaking new ground of artificial intelligence （AI）. The core tasks of this pathway involve the objectification and structured diagnosis-treatment systems， and the construction of a complex， large-scale TCM model. The paper further delineates the data architecture design and reinforcement learning training pathway. Acknowledging the differences in information processing between the human brain and computers， it proposes a training strategy that minimizes manual labeling of "syndromes" and instead focuses on the training paradigm of "herb-human interaction → syndrome manifestation → dosage adjustment". Under the guidance of complexity science theory， TCM is poised for deep integration with AI technology， driving technological innovation powered by data and computational capabilities.
