Perceptions of US Medical Students on Artificial Intelligence in Medicine: Mixed Methods Survey Study
Open accessAbstract
BACKGROUND: Given the rapidity with which artificial intelligence is gaining momentum in clinical medicine, current physician leaders have called for more incorporation of artificial intelligence topics into undergraduate medical education. This is to prepare future physicians to better work together with artificial intelligence technology. However, the first step in curriculum development is to survey the needs of end users. There has not been a study to determine which media and which topics are most preferred by US medical students to learn about the topic of artificial intelligence in medicine. OBJECTIVE: We aimed to survey US medical students on the need to incorporate artificial intelligence in undergraduate medical education and their preferred means to do so to assist with future education initiatives. METHODS: A mixed methods survey comprising both specific questions and a write-in response section was sent through Qualtrics to US medical students in May 2021. Likert scale questions were used to first assess various perceptions of artificial intelligence in medicine. Specific questions were posed regarding learning format and topics in artificial intelligence. RESULTS: We surveyed 390 US medical students with an average age of 26 (SD 3) years from 17 different medical programs (the estimated response rate was 3.5%). A majority (355/388, 91.5%) of respondents agreed that training in artificial intelligence concepts during medical school would be useful for their future. While 79.4% (308/388) were excited to use artificial intelligence technologies, 91.2% (353/387) either reported that their medical schools did not offer resources or were unsure if they did so. Short lectures (264/378, 69.8%), formal electives (180/378, 47.6%), and Q and A panels (167/378, 44.2%) were identified as preferred formats, while fundamental concepts of artificial intelligence (247/379, 65.2%), when to use artificial intelligence in medicine (227/379, 59.9%), and pros and cons of using artificial intelligence (224/379, 59.1%) were the most preferred topics for enhancing their training. CONCLUSIONS: The results of this study indicate that current US medical students recognize the importance of artificial intelligence in medicine and acknowledge that current formal education and resources to study artificial intelligence-related topics are limited in most US medical schools. Respondents also indicated that a hybrid formal/flexible format would be most appropriate for incorporating artificial intelligence as a topic in US medical schools. Based on these data, we conclude that there is a definitive knowledge gap in artificial intelligence education within current medical education in the US. Further, the results suggest there is a disparity in opinions on the specific format and topics to be introduced.
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357 out of 390 respondents (91.5%) agreed that AI training would benefit their future careers.
“357 out of 390 respondents (91.5%) agreeing that AI training would benefit their future careers [32].”
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 [32]
The Results section, “Perspectives on AI in Current Medical Education Curricula,” reports that 91.5% agreed training in AI concepts could be useful for their future careers. The count was 355 of 388 respondents to that question, not 357 of 390; 390 was the total number of students surveyed. (LLM, conf=0.92)
Experimental — accuracy not yet measuredContributions elaborated mainly or solely by medical students strongly call for the inclusion of AI education in medical curricula; students were enthusiastic about learning AI and recognized its crucial role in the future of medicine, but reported a lack of formal AI training and insufficient AI-related learning opportunities; researchers and educators also demanded inclusion of AI in medical Cur
“Finally, contributions elaborated mainly or solely by medical students strongly call for the inclusion of AI education in medical curricula [50–54]. Students were enthusiastic about learning AI and recognized its crucial role in the future of medicine [45, 55]. However, they reported a lack of formal AI training and insufficient AI-related learning opportunities in their medical education [46, 56,”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [45]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredLiu et al. reported that 355 out of 388 participants (91.5%) acknowledged the importance of understanding essential AI concepts within medical education.
“Liu et al. reported that 355 out of 388 participants (91.5%) acknowledged the importance of understanding essential AI concepts within medical education [32].”
A few studies employed either qualitative methods or a mixed-methods approach.
“In contrast, a few of them employed either qualitative methods [38–40] or a mixed-methods approach [41–45].”
From Artificial intelligence in undergraduate medical education: an updated scoping review (2025) · cites this paper as [45]
15 included studies were conducted in high-income countries and the remaining studies in low- and middle-income countries.
“Specifically, 15 studies were conducted in HICs [26–40], while other studies were conducted in LMICs [23, 24, 41–49].”
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“Furthermore, exploration into how US medical students want to learn about AI topics and what specific AI topics they most prefer has not been conducted [25].”
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Cited by
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A scoping review of artificial intelligence in medical education: BEME Guide No. 84
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- Authors
- Liu, D. S., Sawyer, J., Luna, A., Aoun, J., Wang, J., Boachie, L., Halabi, S., & Joe, B.
- Affiliations
- University of Toledo (US)
- Lurie Children's Hospital (US)
- Corresponding author
- Joe, Bina
- ORCID
- Venue
- JMIR Medical Education
- Publisher
- JMIR Publications Inc.
- Published
- 2022-10-21
- Volume
- 8
- Issue
- 4
- Pages
- e38325
- ISSN
- 2369-3762 (ISSN-L)
- PMC
- PMC9636531
- OpenAlex
- W4297812028
- Cited by
- 90
- References
- 10
- Citations by year
- 2026: 29 · 2025: 28 · 2024: 22 · 2023: 10 · 2022: 1
- FWCI
- 4.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Medical Education (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL143082)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- artificial intelligence in healthcare, medical students, undergraduate medical education, student perceptions, hybrid learning formats, elective courses, lecture method, physician-AI collaboration, clinical implementation of AI
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