Curriculum Frameworks and Educational Programs in AI for Medical Students, Residents, and Practicing Physicians:...

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Curriculum Development

Background:

• Successful integration of artificial intelligence (AI) into clinical practice depends on physicians' understanding of AI principles and applications.
• Medical education curricula must incorporate AI topics to equip future physicians with necessary knowledge and skills.
• A significant knowledge gap exists regarding structured AI curriculum frameworks for medical education.

Purpose of the Study:

• To synthesize existing literature on curriculum frameworks and educational programs for teaching AI in medicine.
• To identify current approaches to AI education for medical students, residents, and practicing physicians.

Main Methods:

• A scoping review was conducted following Joanna Briggs Institute methodology.
• Searches were performed in multiple databases (MEDLINE, Embase, CENTRAL, CINAHL, Scopus) and gray literature from 2000 to May 2023.
• Papers describing AI curriculum frameworks in medicine, regardless of country, were included; PRISMA-ScR guidelines were followed.

Main Results:

• Out of 5104 screened papers, 21 met the eligibility criteria.
• Nineteen papers described 30 educational programs, while two described elements of curriculum frameworks.
• Only one general AI curriculum framework and one specialized framework for ophthalmology were identified; no guiding theories or pedagogies were described.

Conclusions:

• This review highlights recent advancements but also a scarcity of comprehensive AI curriculum frameworks in medical education.
• Future research should focus on multidisciplinary approaches to curriculum redesign and dialogue on AI integration.
• Development, deployment, and appraisal of innovative AI educational programs require further investigation.