JCERJournal of Contemporary Educational Research2208-84662208-8474Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jcer.v9i6.10489ArticleArtificial Intelligence in Diagnostics of Traditional Chinese Medicinehttps://artdesignp.com/journal/JCER/9/6/10.26689/jcer.v9i6.10489WangTingye,WangXuemei,WeiNingyi,HeDan2025962025-06-30With the rapid development of science and technology, the application of artificial intelligence (AI) technology in medical education has become increasingly widespread in the digital age, bringing new opportunities and challenges to China’s higher education of traditional Chinese medicine (TCM). In the context of digital education, it is of great significance to construct a teaching model that integrates AI technology with the characteristics of the diagnostics of traditional Chinese medicine, in order to improve the quality of curriculum teaching in the future. This article aims to introduce how to organically integrate AI technology with diagnostics of traditional Chinese medicine teaching based on the characteristics of the discipline, to achieve teaching mode reform, therefore to improve the teaching quality of traditional Chinese medicine education, and cultivate high-quality TCM talents that meet the needs of the new era.

Feng T, Liu J, Huang L, et al., 2024, Digital Education: Application, Sharing, and Innovation——Overview of the 2024 World Digital Education Conference. China Educational Technology, (03): 20–36.

Cai W, Shen W, 2024, Application of AI-Assisted Teaching Method in Teaching Reform of Acupuncture and Moxibustion. Journal of Traditional Chinese Medicine Management, 32(11): 19–21.

Feng C, Kong Y, Nie G, 2024, Exploring the Application of BOPPPS Teaching Mode in the Teaching of Diagnostics of Traditional Chinese Medicine. Journal of Henan Medical College, 36(04): 552–554.

Duan J, Xiong G, Wei N, 2024, Research on the Reform of the Layered Teaching Mode of Diagnostics of Traditional Chinese Medicine under the Background of Credit System. Chinese Medicine Modern Distance Education of China, 22(13): 1–3.

Gu R, Gu X, 2024, Application of Large Language Models in the Teaching of Traditional Chinese Medicine Diagnostics. Chinese Journal of Medicinal Guide, 26(07): 737–741.

Du C, Zhao Y, Li J, et al., 2014, Exploration of the Mode of Introducing Misdiagnosis Case Analysis into the Teaching of Diagnostics of Traditional Chinese Medicine. Shanxi Journal of Traditional Chinese Medicine, 30(05): 55–56.

Guo H, 2021, Construction of Knowledge Graph for the Online Course in Colleges and Universities Based on Intelligent Education——A Case Study on Chinese Medical History. China Educational Technology, (02): 123–130.

Chu L, Tao T, Chen G, et al., 2024, Learning Resource Recommendation Model of Treatise on Febrile Diseases Course Based on Knowledge Graph. Modern Information Technology, 8(16): 182–188.

Ma J, Gao X, Cui S, 2024, Preliminary Exploration of Intelligent Teaching Construction for “Basic Theory of Traditional Chinese Medicine” Based on Knowledge Graph and Web Quest. Journal of Traditional Chinese Medicine Management, 32(10): 18–20.

Wang J, Ye Z, 2022, Review on the Application of Artificial Intelligence Technology in the Field of Traditional Chinese Medicine Diagnosis. Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology, 24(02): 810–814.

Li B, Li W, Pan H, et al., 2020, Study about the Influence of Artificial Intelligence on the Diagnosis and Treatment of Traditional Chinese Medicine. Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology, 22(05): 1624–1628.

Weidener L, Fischer M, 2023, Teaching AI Ethics in Medical Education: A Scoping Review of Current Literature and Practices. Perspect Med Educ, 12(1): 399–410.