Author(s)

Linlin Zhang ^1,2, Xinwei Zhao ^1,2, Zhengyuan Liu ^1,2, Huiling Wen ^1,2, Miaomiao Liu ^1,2

Affiliation(s)

¹ Tianjin University of Chinese Medicine, Tianjin, 300193, China
² The Second Affiliated Hospital of Tianjin University of Chinese Medicine, Tianjin, 300150, China

Corresponding Author

Linlin Zhang

ABSTRACT

With the rapid development of artificial intelligence technology, its application in medical education provides a new development path for the training of master's and doctoral students in traditional Chinese medicine. This paper analyzes the characteristics of high-level talent cultivation in traditional Chinese medicine and the demand for the intervention of artificial intelligence, and explores its application methods in theoretical teaching, clinical practical training, scientific research training, and cultivation management. Artificial intelligence can promote personalized learning, syndrome differentiation thinking training, scientific research efficiency improvement, and optimization of cultivation quality evaluation through technologies such as knowledge graphs, generative large models, virtual cases, and data analysis. At the same time, the paper points out that the application of artificial intelligence still faces risks such as knowledge distortion, algorithmic bias, academic integrity, data security, and over-reliance. In the future, the principle of "enhancement rather than replacement" should be upheld, and the construction of specialized knowledge bases, the cultivation of artificial intelligence literacy, and standardized governance should be strengthened to promote the deep integration of artificial intelligence with the training patterns of Traditional Chinese Medicine graduate students.

KEYWORDS

Artificial intelligence; Traditional Chinese Medicine master's and doctoral student training; Intelligent assisted teaching

CITE THIS PAPER

Linlin Zhang, Xinwei Zhao, Zhengyuan Liu, Huiling Wen, Miaomiao Liu. Exploration of the Application Methods of Artificial Intelligence-Assisted Teaching in the Training of Master's and Doctoral Students in Traditional Chinese Medicine. Adult and Higher Education (2026). Vol. 8, No. 3, 1-9. DOI: http://dx.doi.org/10.23977/aduhe.2026.080301.

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