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.

KKB reports grants from the Wilhelm Sander Foundation and receives speaker fees from Canon Medical Systems Corporation. KKB is a member of the advisory board of the EU Horizon 2020 LifeChamps project (875329) and the EU IHI project IMAGIO (101112053). MA reports consultant fees from Segmed, Inc. The competing interests had no role in the study design, data collection and analysis, manuscript preparation, or decision to publish. All other authors declare no financial or non-financial competing interests.

This research is funded by the European Union (COMFORT (Computational Models FOR patienT stratification in urologic cancers - Creating robust and trustworthy multimodal AI for health care), project number: 101079894, authors involved: FB, MRM, LCA, PDB, AB, RC, GDV, VD, AH, LJ, GK, AL, PS, principal investigator: KKB, sponsors' website: https://www.comfort-ai.eu). Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union. The European Union cannot be held responsible for them. The funding had no role in the study design, data collection and analysis, manuscript preparation, or decision to publish.

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This multicenter cross-sectional study received ethical approval from the Institutional Review Board at Charité - University Medicine Berlin (EA4/213/22), serving as the principal institution, in compliance with the Declaration of Helsinki and its later amendments. To ensure participant anonymity, the necessity for informed consent was waived.

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Upon acceptance of the peer-reviewed article, the collected and analyzed dataset will be publicly available under CC-BY 4.0 license: Busch F, Hoffmann L, Truhn D, Ortiz-Prado E, Makowski MR, Bressem KK, et al. Dataset: Medical students' perceptions towards artificial intelligence in education and practice: A multinational, multicenter cross-sectional study. Database: figshare [Internet]. doi:10.6084/m9.figshare.24422422 [Reserved]. For peer review, a private anonymized link is provided.