Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception
Open accessAbstract
Background: The emerging field of artificial intelligence (AI) will probably affect the practice for the next generation of doctors. However, the students' views on AI have not been largely investigated. Methods: An anonymous electronic survey on AI was designed for medical and dental students to explore: (1) sources of information about AI, (2) AI applications and concerns, (3) AI status as a topic in medicine, and (4) students' feelings and attitudes. The questionnaire was advertised on social media platforms in 2020. Security measures were employed to prevent fraudulent responses. Mann-Whitney U -test was employed for all comparisons. A sensitivity analysis was also performed by binarizing responses to express disagreement and agreement using the Chi-squared test. Results: Three thousand one hundred thirty-three respondents from 63 countries from all continents were included. Most respondents reported having at least a moderate understanding of the technologies underpinning AI and of their current application, with higher agreement associated with being male ( p < 0.0001), tech-savvy ( p < 0.0001), pre-clinical student ( p < 0.006), and from a developed country ( p < 0.04). Students perceive AI as a partner rather than a competitor (72.2%) with a higher agreement for medical students ( p = 0.002). The belief that AI will revolutionize medicine and dentistry (83.9%) with greater agreement for students from a developed country ( p = 0.0004) was noted. Most students agree that the AI developments will make medicine and dentistry more exciting (69.9%), that AI shall be part of the medical training (85.6%) and they are eager to incorporate AI in their future practice (99%). Conclusion: Currently, AI is a hot topic in medicine and dentistry. Students have a basic understanding of AI principles, a positive attitude toward AI and would like to have it incorporated into their training.
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Bisdas et al. reported that 2,683 out of 3,133 students (85.6%) perceived AI as a partner in medical practice.
“Bisdas et al. reported that 2,683 out of 3,133 students (85.6%) perceived AI as a partner in medical practice [23]”
From Is it time to introduce an artificial intelligence curriculum in undergraduate medical education? medical students’ perspectives: a systematic review and meta-analysis (2026) · cites this paper as [23]
The Results section, “Attitudes and Feelings Toward AI,” reports that 2,261 students (72.2%) perceived AI as a partner rather than a competitor. The cited figure of 2,683 (85.6%) refers instead to students who agreed AI should be part of core medical training. (LLM, conf=0.92)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredA study analyzing both medical and dental students' perceptions reported that 72% believed AI would revolutionize medicine and dentistry, a view held more often by students from developed countries than those from other countries.
“A study analyzing both medical and dental students’ perceptions of AI reported that 72% of them believed that AI would revolutionize medicine and dentistry, a view held more often by students from developed countries than those from other countries [74].”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [74]
The Results section, “Attitudes and Feelings Toward AI,” reports that 83.9%, not 72%, believed AI would revolutionize medicine and dentistry, with greater agreement among students from developed countries (p = 0.0004). The 72.2% figure refers instead to students who perceived AI as a partner rather than a competitor. (LLM, conf=0.94)
Experimental — accuracy not yet measuredRather than replacing human physicians, students perceived AI as a collaborative partner in medical practice.
“Generally, rather than replacing human physicians, students perceived AI as a collaborative partner in medical practice [73, 74].”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [74]
Multiple articles have recommended various AI-related competencies or identified areas for learning about AI literacy in UGME.
“Multiple articles have recommended various AI-related competencies or identified areas for learning about AI literacy in UGME [39, 74, 159, 160].”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [74]
Medical students want AI incorporated into their formal medical curriculum.
“As both this study and previous surveys have confirmed that medical students want AI incorporated into their formal medical curriculum, any such changes should be well received by the undergraduate medical learner population [7, 17].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [17]
The study's findings are consistent with previous studies that identified limited knowledge of AI among medical trainees.
“Our findings are consistent with previous studies of medical learners, which have also identified limited knowledge of AI among medical trainees [7, 8, 16, 17].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [17]
Medical students are often not familiar with AI and may be worried about the potential for job loss.
“Previous studies have shown that medical students are often not familiar with AI and may be worried about the potential for job loss [13–15].”
From AI in medical education: medical student perception, curriculum recommendations and design suggestions (2023) · cites this paper as [14]
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Artificial Intelligence in Medical Education- Perception Among Medical Students
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“%) perceived AI as a partner in medical practice [23], reflecting optimism about AI’s role in medicine [44].”
Influential
- Authors
- Bisdas, S., Topriceanu, C.-C., Zakrzewska, Z., Irimia, A.-V., Shakallis, L., Subhash, J., Casapu, M.-M., Leon-Rojas, J., Pinto dos Santos, D., Andrews, D. M., Zeicu, C., Bouhuwaish, A. M., Lestari, A. N., Abu-Ismail, L., Sadiq, A. S., Khamees, A., Mohammed, K. M. G., Williams, E., Omran, A. I., Ismail, D. Y. A., & Ebrahim, E. H.
- Affiliations
- University College London Hospitals NHS Foundation Trust (GB)
- University College London (GB)
- University of Nottingham (GB)
- Carol Davila University of Medicine and Pharmacy (RO)
- Cardiff University (GB)
- Bandung Islamic University (ID)
- CMH Lahore Medical College and Institute of Dentistry (PK)
- Yarmouk University (JO)
- Tanta University (EG)
- University of Plymouth (GB)
- Tobruk University (LY)
- Hashemite University (JO)
- Sebha University (LY)
- Corresponding author
- Bisdas, Sotirios
- ORCID
- Venue
- Frontiers in Public Health
- Publisher
- Frontiers Media SA
- Published
- 2021-12-24
- Volume
- 9
- Pages
- 795284-795284
- ISSN
- 2296-2565 (ISSN-L)
- PMC
- PMC8739771
- OpenAlex
- W4200473452
- Cited by
- 232
- References
- 35
- Citations by year
- 2026: 65 · 2025: 59 · 2024: 67 · 2023: 28 · 2022: 12
- FWCI
- 7.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Greater South Information System
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- artificial intelligence in healthcare, medical students, dental students, student attitudes toward AI, AI literacy, artificial intelligence in medical education, artificial intelligence in dentistry
- MeSH terms
- Artificial Intelligence, Female, Humans, Male, Perception, Surveys and Questionnaires, Students, Dental, Students, Medical
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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