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Artificial Intelligence Empowered Teaching Reform of Anatomy Courses Under Medical-Engineering Integration: Practice, Evaluation, and Reflection



Author(s)

WANG Yan, SUI Li, CAI Yusi, CHEN Changle*

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DOI:10.17265/2161-623X/2026.04.002

University of Shanghai for Science and Technology, Shanghai, China； Shanghai Qigong Research Institute, Shanghai, China

With the rapid advancement of artificial intelligence (AI), medical education is undergoing profound transformation, particularly within the context of medical-engineering integration. Traditional lecture-based anatomy teaching is increasingly insufficient to meet the demands of interdisciplinary talent cultivation. This study explores the reform of an undergraduate anatomy course for biomedical engineering students through the integration of AI-assisted teaching tools and pedagogical innovation. A cohort of approximately 190 students participated in a 48-hour anatomy course in which the curriculum design, teaching content, instructional methods, and evaluation strategies were systematically restructured. AI-supported platforms, virtual simulation technologies, and case-based learning approaches were introduced through an incremental integration model. It was demonstrated that the reform was associated with significant improvements in student engagement, spatial understanding of anatomical structures, and higher-order learning outcomes in application-oriented tasks. Meanwhile, teaching management was facilitated and data-driven feedback was enabled through AI technologies, although increased demands were placed on teachers’ digital competence. Overall, the integration of AI into anatomy teaching is feasible and shows positive effects. However, further refinement in curriculum design, evaluation systems, and teacher training is necessary to ensure sustainable implementation. This study may provide useful references for teaching reform in basic medical courses under the background of medical-engineering integration.

artificial intelligence, medical-engineering integration, anatomy course, teaching reform, medical education

WANG Yan, SUI Li, CAI Yusi, CHEN Changle*. (2026). Artificial Intelligence Empowered Teaching Reform of Anatomy Courses Under Medical-Engineering Integration: Practice, Evaluation, and Reflection. US-China Education Review A, April 2026, Vol. 16, No. 4, 196-202.