Medical students’ perceptions towards artificial intelligence in education and practice: A multinational, multicenter cross-sectional study
Abstract
Abstract Background Artificial intelligence (AI) is anticipated to fundamentally change the educational and professional landscape for the next generation of physicians, but its successful integration depends on the global perspectives of all stakeholders. Previous medical student surveys were limited by small sample sizes or geographic constraints, hindering a global comparison of perceptions. This study aims to explore current medical students’ attitudes towards AI in medical education and the profession on a broad, international scale and to examine regional differences in perspectives. Methods and Findings This international multicenter cross-sectional study developed and validated an anonymous online survey of 15 multiple-choice items to assess medical, dentistry, and veterinary students’ AI knowledge and attitudes toward the utilization of AI in healthcare, the current state of AI education, and regional differences in perspectives. Between April and October 2023, 4,313 medical, 205 dentistry, and 78 veterinary students from 192 faculties in 48 countries responded to the survey (average response rate: 0.2%, standard deviation: 0.4%). Most participants studied in European countries (N=2,350), followed by North/South America (N=1,070) and Asia (N=944). Students expressed predominantly positive attitudes towards the use of AI in healthcare (67.6%, N=3,091) and the desire for more AI teaching in their curricula (76.1%, N=3,474). However, they reported limited general knowledge of AI (75.3%, N=3,451), the absence of AI-related courses (76.3%, N=3,497), and felt inadequately prepared to use AI in their future careers (57.9%, N=2,652). The subgroup analyses revealed regional differences in perceptions, although predominantly with small effect sizes. The main limitations include the low response rate per institution, which was calculated on total enrollment across all degree programs, and the risk of selection bias. Conclusions This study highlights the favorable perceptions of international medical students towards incorporating AI in healthcare practice while emphasizing the importance of integrating AI teaching into medical education. Graphical abstract
Authors 7
-
Felix Busch corresponding
Charité - Universitätsmedizin Berlin · Freie Universität Berlin
Affiliation as printed
Department of Radiology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universitätzu Berlin, Berlin, Germany
-
Charité - Universitätsmedizin Berlin · Freie Universität Berlin
Affiliation as printed
Department of Radiology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universitätzu Berlin, Berlin, Germany
-
Affiliation as printed
Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany
-
Affiliation as printed
One Health Research Group, Universidad de Las Américas, Quito, Ecuador
-
Technical University of Munich
Affiliation as printed
Department of Radiology, Technical University of Munich, Munich, Germany
-
Charité - Universitätsmedizin Berlin · Freie Universität Berlin · Berlin Institute of Health at Charité - Universitätsmedizin Berlin
Affiliation as printed
Berlin Institute of Health at Charité – Universitätsmedizin Berlin, Berlin, Germany
Department of Radiology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universitätzu Berlin, Berlin, Germany
-
Technical University of Munich
Affiliation as printed
Department of Radiology, Technical University of Munich, Munich, Germany
Cited by 13 stored of 13
13 results
No patents citing this paper on Lens.org (checked 2026-10-06).