# The Role of AI in Shaping Medical Education: Insights from an Umbrella Review of Review Studies

## TL;DR

This paper reviews how AI is being used in medical education and identifies six key areas where it is making an impact.

## Contribution

The study provides a comprehensive umbrella review of AI applications in medical education from 2018 to 2024.

## Key findings

- Six key themes of AI applications in medical education were identified: faculty, students, teaching, assessment, curriculum, and management.
- Management and implementation had the highest representation among the themes.
- China led in AI-related publications in medical education, with three journals being the main venues.

## Abstract

Artificial intelligence (AI) has become integral to various fields, including medical education. This study explores AI applications in medical education through a review of relevant studies.

Using the umbrella review method, this study synthesized findings from reviews conducted between 2018 and 2024. The PRISMA framework guided a comprehensive search of databases, including Science Direct, Springer, ERIC, PubMed, and Google Scholar. After quality assessment with the CASP framework, 77 systematic review articles were selected. Data analysis employed Elo and Kyngäs’s qualitative content analysis approach, supported by expert validation and researcher consensus.

Six key themes of AI applications in medical education were identified: faculty, students, teaching and learning process, assessment, curriculum, and management/implementation. Management and implementation had the highest representation (26.5%), followed by teaching and learning processes (25.9%). Examples of each theme were highlighted. China produced the most articles, and three journals—International Journal of Educational Technology in Higher Education,
Computers and Education: Artificial Intelligence, and Education and Information Technologies—were the leading publication venues.

These six themes provide a roadmap for medical education policymakers to adapt to AI advancements. Emphasizing management and executive applications, the findings predict significant changes in the future of medical education and practice. This framework can help medical universities align curricula and operations with the evolving landscape of AI in healthcare.