Artificial Intelligence in Distance Medical Learning: A Comprehensive Review
Abstract:
Background: The increasing demand for global healthcare professionals necessitates scalable, high-quality medical training. Distance learning models, accelerated by global public health demands, require novel ped agogical tools to bridge the gap between virtual instruction and complex clinical reality. Artificial Intelligence (AI) technologies offer a transformative solution.
Objective: This systematic review aims to comprehensively evaluate the current landscape of AI integration in distance medical education, analyze its impact across key educational domains (cognition, psychomotor skills, assessment), and critically appraise the associated ethical, logistical, and pedagogical challenges [1-10].
Methodology: A systematic search and synthesis of high-impact studies, systematic reviews, and consensus pa pers published between January 2020 and October 2025 were conducted, utilizing databases such as PubMed, ERIC, and Scopus. Inclusion criteria prioritized studies reporting empirical data on educational outcomes or rigorous theoretical frameworks for AI deployment in fully remote or hybrid medical and health professions education. The findings were categorized using a modified PRISMA-ScR structure focused on AI function and educational impact.
