ReviewJournal of advances in medical education & professionalism2025
The Role of AI in Shaping Medical Education: Insights from an Umbrella Review of Review Studies.
Review in Journal of advances in medical education & professionalism, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Benchmarking Large Language Models for Scientific Writing: A Mixed‑Methods Evaluation of Chatgpt, Deepseek, and Human Authors.Journal of advances in medical education & professionalism · 2026Article
- Mapping Personalized Learning in Medical Education: A Meta-Synthesis of Artificial Intelligence Applications.Journal of advances in medical education & professionalism · 2026Review
- AI as a differentiated cognitive partner in medical education: a comparative study of popular science versus research-based curriculum extensions in histology and embryology.BMC medical education · 2026Article
- Efficacy of Large Language Models in Providing Evidence-Based Patient Education for Celiac Disease: A Comparative Analysis.Nutrients · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: 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. Methods: 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. Results: 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. Conclusion: 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.