Mapping the use of artificial intelligence in medical education: a scoping review
Authors:
- Erwin Hernando Hernández RincónErwin Hernando Hernández Rincón
- Daniel JimenezDJDaniel Jimenez
- Lizeth Alexandra Chavarro AguilarLALizeth Alexandra Chavarro Aguilar
- Juan Miguel Pérez FlórezJFJuan Miguel Pérez Flórez
- Álvaro Enrique Romero TapiaÁTÁlvaro Enrique Romero Tapia
- Claudia Liliana Jaimes PeñuelaCPClaudia Liliana Jaimes Peñuela
Top Cited Papers
Open Access
- 12 April 2025
- journal article
- review article
- Published by Springer Nature in BMC Medical Education
- Vol. 25 (1) , 1-16
Abstract
The integration of artificial intelligence (AI) in healthcare has transformed clinical practices and medical education, with technologies like diagnostic algorithms and clinical decision support increasingly incorporated into curricula. However, there is still a gap in preparing future physicians to use these technologies effectively and ethically. This scoping review maps the integration of artificial intelligence (AI) in undergraduate medical education (UME), focusing on curriculum development, student competency enhancement, and institutional barriers to AI adoption. A comprehensive search in PubMed, Scopus, and BIREME included articles from 2019 onwards, limited to English and Spanish publications on AI in UME. Exclusions applied to studies focused on postgraduate education or non-medical fields. Data were analyzed using thematic analysis to identify patterns in AI curriculum development and implementation. A total of 34 studies were reviewed, representing diverse regions and methodologies, including cross-sectional studies, narrative reviews, and intervention studies. Findings revealed a lack of standardized AI curriculum frameworks and notable global discrepancies. Key elements such as ethical training, collaborative learning, and digital competence were identified as essential, with an emphasis on transversal skills that support AI as a tool rather than a standalone subject. This review underscores the need for a standardized, adaptable AI curriculum in UME that prioritizes transversal skills, including digital competence and ethical awareness, to support AI's gradual integration. Embedding AI as a practical tool within interdisciplinary, patient-centered frameworks fosters a balanced approach to technology in healthcare. Further regional research is recommended to develop frameworks that align with cultural and educational needs, ensuring AI integration in UME promotes both technical and ethical competencies.Keywords
Funding Information
- Universidad de La Sabana (MED-342-2023, MED-342-2023, MED-342-2023, MED-342-2023, MED-342-2023, MED-342-2023)
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