First Working Meeting of the Special Project “Artificial Intelligence and the Paradigm Shift in Traditional Chinese Medicine Research: Oppor

Date: April 14, 2025

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On April 10, 2025, the first working meeting of the special research project “Artificial Intelligence and the Paradigm Shift in Traditional Chinese Medicine (TCM) Research: Opportunities and Challenges” was successfully held. The meeting was attended and addressed by Prof. Gu Ning, Academician of the Chinese Academy of Sciences and Principal Investigator of the project, and brought together more than 50 experts from institutions including Peking University, Beijing University of Chinese Medicine, Nanjing University of Chinese Medicine, University of Science and Technology Beijing, Nanjing University, University of Chinese Academy of Sciences, Dalian Medical University, Chengde Medical University, and the CAS Institute of Nanoscience and Technology. The meeting was chaired by Prof. Han Hongbin of Peking University.

At the opening of the meeting, Academician Gu Ning introduced the project’s background and significance on behalf of the research team. He emphasized that, in the context of ongoing reforms in China’s scientific and technological system, the National Natural Science Foundation of China has launched a special initiative on the paradigm shift in TCM research through artificial intelligence. The aim is to leverage modern information technologies and AI models to promote the digital transformation of TCM, enabling in-depth exploration of traditional Chinese medicine within its historical context and constructing a modern scientific framework for expressing TCM theories. This meeting marked a step forward in refining the project proposal, clarifying research directions, and identifying implementation pathways.

Experts’ presentations

Prof. Zhou Xiaohua presented a report titled “A TCM Information Research Framework Based on Causal Inference and Large Language Models”, proposing the use of causal inference to address limitations in the application of large language models to TCM.

Prof. Li Yi introduced a TCM Ontology and Knowledge Graph Research Plan, focusing on improving knowledge representation and reasoning capabilities to enhance semantic understanding by AI models, while offering suggestions for subsequent research tasks.

Prof. Zhuo Li delivered a report on “Key Scientific and Technical Challenges in Developing Large TCM Models”, discussing how to translate TCM's intrinsic dialectical thinking, unstructured experiential knowledge, and complex reasoning into computable and interpretable models that support the expression of core TCM principles.

Dr. Lan Tian, on behalf of the research team led by Prof. Zeng Yide, shared recent progress in the theoretical foundations of TCM information science. Prof. Zeng emphasized that many current AI modeling approaches for traditional Chinese medicine are still based on Western biomedical logic, which fails to capture the uniqueness of TCM, thus calling for a paradigm shift in methodology.