Global research trends and thematic developments in artificial intelligence applications in medical education: a bibliometric study

Purpose: Artificial intelligence (AI) is rapidly transforming medical education through innovative methods in instruction, assessment, and simulation. This study systematically analyzes global research trends and thematic developments in AI applications within medical education.Methods: A total of 732 English-language articles were identified in the Scopus database prior to April 10, 2025, using the keywords “medical education” and “artificial intelligence” within titles, abstracts, or keywords. Bibliometric analysis was conducted using VOSviewer to investigate publication trends, keyword co-occurrence, and citation coupling, complemented by cluster-based content analysis. Additional analyses included publication characteristics, regional distribution, author collaboration, and the evolution of core topics.Results: Publication output increased markedly after 2018, reaching a peak in 2024. The United States, China, and the United Kingdom were leaders in research volume, while smaller nations such as Ireland and Singapore exhibited high citation impact. Author analysis demonstrated robust collaboration networks and a growing trend of interdisciplinary engagement. Keyword clustering revealed four primary themes: AI-driven simulation and training, intelligent assessment systems, personalized learning environments, and ethical and pedagogical considerations. The average year of keyword publication (2023–2024) underscores the recent acceleration of the field, particularly in generative AI and large language models.Conclusion: The integration of AI in medical education is accelerating, characterized by thematic diversification and broader global participation. This study provides a comprehensive overview of the field’s intellectual landscape and highlights critical areas for future advancement, including curriculum reform, faculty development, and responsible AI integration to optimize educational outcomes and learner preparedness.

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Publication Details

Journal
Science Editing
Published
2025-08-04
DOI
https://doi.org/10.6087/kcse.373
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Global research trends and thematic developments in artificial intelligence applications in medical education: a bibliometric study

Dhakir Abbas Ali, Oyyappan Duraipandi, Bo Wang
Science Editing
Artificial Intelligence in Healthcare and Education
article

Global research trends and thematic developments in artificial intelligence applications in medical education: a bibliometric study

Dhakir Abbas Ali, Oyyappan Duraipandi, Bo Wang
article en

Abstract

Purpose: Artificial intelligence (AI) is rapidly transforming medical education through innovative methods in instruction, assessment, and simulation. This study systematically analyzes global research trends and thematic developments in AI applications within medical education.Methods: A total of 732 English-language articles were identified in the Scopus database prior to April 10, 2025, using the keywords “medical education” and “artificial intelligence” within titles, abstracts, or keywords. Bibliometric analysis was conducted using VOSviewer to investigate publication trends, keyword co-occurrence, and citation coupling, complemented by cluster-based content analysis. Additional analyses included publication characteristics, regional distribution, author collaboration, and the evolution of core topics.Results: Publication output increased markedly after 2018, reaching a peak in 2024. The United States, China, and the United Kingdom were leaders in research volume, while smaller nations such as Ireland and Singapore exhibited high citation impact. Author analysis demonstrated robust collaboration networks and a growing trend of interdisciplinary engagement. Keyword clustering revealed four primary themes: AI-driven simulation and training, intelligent assessment systems, personalized learning environments, and ethical and pedagogical considerations. The average year of keyword publication (2023–2024) underscores the recent acceleration of the field, particularly in generative AI and large language models.Conclusion: The integration of AI in medical education is accelerating, characterized by thematic diversification and broader global participation. This study provides a comprehensive overview of the field’s intellectual landscape and highlights critical areas for future advancement, including curriculum reform, faculty development, and responsible AI integration to optimize educational outcomes and learner preparedness.

Science EditingVol. 12(2)
Lincoln University College (MY)
Quality Education
Openalex Percentile: Top 86%
Artificial Intelligence in Healthcare and Education
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