Artificial intelligence curriculum in medical education: a Canadian cross-sectional mixed-methods study

Abstract

Emerging artificial intelligence (AI) technologies have diverse applications in medicine. As AI tools advance towards clinical implementation, skills in how to use and interpret AI in a healthcare setting could become integral for physicians. We deployed a 56 question survey to all 17 Canadian medical schools that assessed currently available learning opportunities about AI, the perceived need for AI education, and barriers to educating about AI among undergraduate medical students. Additionally, interviews were conducted with participants to provide narrative context, and analyzed using thematic analysis. The authors received 475 responses from students at 17 of 17 Canadian medical schools. Likert scale survey questions were scored from 1 (disagree) to 5 (agree). Respondents agreed that AI applications in medicine would become common in the future (3.80 ± 0.38) and would improve medicine (3.71 ± 0.54). Further, respondents agreed that they would need to use and understand AI during their medical careers (3.76 ± 0.572; 3.43 ± 0.773), and that AI should be formally taught in medical education (3.43 ± 0.756). In contrast, a significant number of participants indicated that they did not have any formal educational opportunities about AI (1.76 ± 785) and that AI-related learning opportunities were inadequate (2.12 ± 0.802). Interviews with 18 students were conducted, with emerging themes including a lack of formal education opportunities and logistical challenges in adding AI to curriculum. Given that medical students overwhelmingly belief that AI is important to the future of medicine, and the progression of AI tools towards clinical implementation, AI should be considered for inclusion in formal medical curriculum.