JMIR Publications

ABSTRACT

Background:

The rapid integration of artificial intelligence (AI) and medical big data into health care is transforming diagnostic accuracy, treatment planning, and research capabilities. Despite these developments, formal AI and medical big data education is limited in undergraduate medical curricula, particularly in China.

Objective:

This study aimed to investigate clinical medical undergraduates’ familiarity with AI and medical big data, their perceived need for relevant courses, and their preferred curriculum design and assessment methods.

Methods:

A cross-sectional, web-based survey was administered to students in the five-year clinical medicine program at a medical university in China from January 10 to January 17, 2025.The self-administered questionnaire was developed through a comprehensive literature review, and its content validity was assessed by experts in medical education and artificial intelligence.Descriptive statistics summarized participant demographics and survey responses. Two-way-ANOVA was performed to evaluate differences in grade and gender.

Results:

A total of 871 clinical medicine undergraduates participated in the study (62.6% female).While 36% of the students agreed or strongly agreed that they were familiar with the application of artificial intelligence and medical big data in the healthcare field, only 32.6% had prior learning experience in this area.A total of 94% of the students indicated that a course on artificial intelligence and medical big data is needed in their undergraduate curriculum.65% of the students indicated that if a course on artificial intelligence and medical big data is offered, they would prefer personalized teaching based on the textbook, and 73% expressed a preference for open-book examinations. Significant differences in perceptions and curriculum preferences were observed across gender and grade (P < 0.05).

Conclusions:

This study reveals a strong demand among clinical medicine undergraduates for AI and medical big data education. Even with limited prior experience,students showed clear interest and preferences,emphasizing the need for curriculum adjustments to forster data-driven health care.