Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes.

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Health Informatics

Background:

• Healthcare is entering the Artificial Intelligence (AI) era, necessitating human-machine interaction for clinical decisions.
• Medical students require proficiency in AI's benefits (cost, quality, access) and drawbacks (bias, transparency, liability).
• A lack of research exists on effectively integrating AI into medical education curricula.

Purpose of the Study:

• To review current literature on medical students' attitudes toward AI.
• To examine AI implementation in medical curricula.
• To identify research gaps and advocate for curriculum changes.

Main Methods:

• An integrative review of 39 articles published between 2010 and 2020.
• Searches conducted on Pubmed, Medline, Google Scholar, and Web of Science.
• Analysis using the Technology Acceptance Model and Diffusion of Innovations theory, with quantitative data analysis.

Main Results:

• Only 5 articles assessed medical students' attitudes toward AI.
• Few plans (6) and even fewer implementations (2) of AI in curricula were reported.
• A significant majority of articles (26) emphasized the need for more research and curriculum adaptation.

Conclusions:

• Current integration of AI in medical education is minimal, with few reported plans or implementations.
• Medical schools must collaborate on longitudinal studies and initiatives to prepare students in AI.
• Equipping future physicians with AI knowledge is crucial for advancing healthcare.