Impact of artificial intelligence on US medical students' choice of radiology
Abstract
Purpose International student surveys have shown significant anxiety about pursuing radiology as a career due to artificial intelligence (AI). For a counterpart study in the US, we examined the impact of AI on US medical students' choice of radiology as a career, and how such impact is influenced by students' opinions on and exposures to AI and radiology.Methods Students across 32 US medical schools participated in an anonymous online survey. The respondents' radiology ranking with and without AI were compared. Among those considering radiology within their top 3 choices, change in radiology ranking due to AI was statistically examined for association with baseline characteristics, subjective opinions, and prior exposures.Results AI significantly lowered students' preference for ranking radiology (P < .001). One-sixth of students who would have chosen radiology as the first choice did not do so because of AI, and approximately half of those considering radiology within their top 3 choices remained concerned about AI. Ranking radiology lower due to AI was associated with greater concerns about AI (P < .001), less perceived understanding of radiology (P = .02), predicting a decrease in job opportunities (P < .001), and exposure to AI through medical students/family (P = .03) as well as through radiology attendings and residents (P = .03). Education on AI during radiology rotations, followed by pre-clinical lectures, was the most preferred way to learn about AI.Conclusion AI has a significantly negative impact on US medical students' choice of radiology as a career, a phenomenon influenced by both individual concerns and exposure to AI from the medical community.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
One study met the NOS criteria for good and 22 studies met the NOS criteria for fair.
“One study met the NOS criteria for good [17] and 22 studies met the NOS criteria for fair [7,8,18–36,37].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [22]
Cites
Pesapane, F., Codari, M., & Sardanelli, F. (2018) · European Radiology Experimental · doi:10.1186/s41747-018-0061-6 · Cited by 839 · see citing works
Medical students' attitude towards artificial intelligence: a multicentre survey
Pinto dos Santos, D., Giese, D., Brodehl, S., Chon, S. H., Staab, W., Kleinert, R., Maintz, D., & Baeßler, B. (2019) · European Radiology · doi:10.1007/s00330-018-5601-1 · Cited by 754 · see citing works
Sit, C., Srinivasan, R., Amlani, A., Muthuswamy, K., Azam, A., Monzon, L., & Poon, D. S. (2020) · Insights into Imaging · doi:10.1186/s13244-019-0830-7 · Cited by 507 · see citing works
Gong, B., Nugent, J. P., Guest, W., Parker, W., Chang, P. J., Khosa, F., & Nicolaou, S. (2019) · Academic Radiology · doi:10.1016/j.acra.2018.10.007 · Cited by 325 · see citing works
What do medical students actually need to know about artificial intelligence?
McCoy, L. G., Nagaraj, S., Morgado, F., Harish, V., Das, S., & Celi, L. A. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0294-7 · Cited by 240 · see citing works
Artificial Intelligence: Threat or Boon to Radiologists?
Recht, M., & Bryan, R. N. (2017) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2017.07.007 · Cited by 172 · see citing works
Artificial Intelligence in Radiology: Current Technology and Future Directions
Zoga, A. C., & Syed, A. (2018) · Seminars in Musculoskeletal Radiology · doi:10.1055/s-0038-1673383 · Cited by 170 · see citing works
Medical Student Perspectives on the Impact of Artificial Intelligence on the Practice of Medicine
Park, C. J., Yi, P. H., & Siegel, E. L. (2021) · Current Problems in Diagnostic Radiology · doi:10.1067/j.cpradiol.2020.06.011 · Cited by 167 · see citing works
van Hoek, J., Huber, A. T., Leichtle, A. B., Härmä, K., Hilt, D., von Tengg‐Kobligk, H., Heverhagen, J. T., & Poellinger, A. (2019) · European Journal of Radiology · doi:10.1016/j.ejrad.2019.108742 · Cited by 124 · see citing works
Surveying Fourth-Year Medical Students Regarding the Choice of Diagnostic Radiology as a Specialty
Arleo, E. K., Bluth, E. I., Francavilla, M. L., Straus, C. M., Reddy, S., & Recht, M. P. (2015) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2015.08.005 · Cited by 81 · see citing works
Radiology in 2018: Are You Working with AI or Being Replaced by AI?
Bluemke, D. A. (2018) · Radiology · doi:10.1148/radiol.2018184007 · Cited by 45 · see citing works
Artificial Intelligence, Radiology, and the Way Forward
Jalal, S., Nicolaou, S., & Parker, W. (2019) · Canadian Association of Radiologists Journal · doi:10.1016/j.carj.2018.09.004 · Cited by 35 · see citing works
Yen, A., Webb, E. M., Jordan, E. J., Kallianos, K. G., & Naeger, D. M. (2018) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2018.03.006 · Cited by 29 · see citing works
Lee, H., Kim, D. H., & Hong, P. (2019) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2019.11.026 · Cited by 25 · see citing works
Self-citationArtificial Intelligence in Radiology: Resident Recruitment Help or Hindrance?
Grayev, A. M. (2019) · Academic Radiology · doi:10.1016/j.acra.2019.01.005 · Cited by 11 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A scoping review of artificial intelligence in medical education: BEME Guide No. 84
Gordon, M., Daniel, M., Ajiboye, A., Uraiby, H., Xu, N. Y., Bartlett, R., Hanson, J., Haas, M., Spadafore, M., Grafton-Clarke, C., et al. (2024) · Medical Teacher · doi:10.1080/0142159x.2024.2314198 · Cited by 543 · see citing works
Chen, M., Zhang, B., Cai, Z., Seery, S., Gonzalez, M. J., Ali, N. M., Ren, R., Qiao, Y., Xue, P., & Jiang, Y. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.990604 · Cited by 258 · see citing works
Mousavi Baigi, S. F., Sarbaz, M., Ghaddaripouri, K., Ghaddaripouri, M., Mousavi, A. S., & Kimiafar, K. (2023) · Health Science Reports · doi:10.1002/hsr2.1138 · Cited by 255 · see citing works
Clinical applications of artificial intelligence in radiology
Mello-Thoms, C. R., & Mello, C. A. B. (2023) · British Journal of Radiology · doi:10.1259/bjr.20221031 · Cited by 131 · see citing works
The Role of Artificial Intelligence in Medical Education: A Systematic Review
Tozsin, A., Uçmak, H., Soytürk, S., Aydın, A., Gözen, A. S., Fahim, M. M. A., Güven, S., & Ahmed, K. (2024) · Surgical Innovation · doi:10.1177/15533506241248239 · Cited by 96 · see citing works
Pupic, N., Ghaffari-zadeh, A., Hu, R., Singla, R., Darras, K., Karwowska, A., & Forster, B. B. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000255 · Cited by 79 · see citing works
Mezrich, J. L. (2022) · American Journal of Roentgenology · doi:10.2214/ajr.21.27224 · Cited by 75 · see citing works
Gillissen, A., Kochanek, T., Zupanic, M., & Ehlers, J. (2022) · Healthcare · doi:10.3390/healthcare10040723 · Cited by 74 · see citing works
Eltawil, F. A., Atalla, M., Boulos, E., Amirabadi, A., & Tyrrell, P. N. (2023) · Tomography · doi:10.3390/tomography9040115 · Cited by 72 · see citing works
Arvai, N., Katonai, G., & Mesko, B. (2025) · Journal of Medical Internet Research · doi:10.2196/66986 · Cited by 57 · see citing works
The cases for and against artificial intelligence in the medical school curriculum
Ngo, B., Nguyen, D., & vanSonnenberg, E. (2022) · Radiology: Artificial Intelligence · doi:10.1148/ryai.220074 · Cited by 53 · see citing works
Mirkin, S., & Albensi, B. C. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1094233 · Cited by 46 · see citing works
Cheong, R. C. T., Pang, K. P., Unadkat, S. N., Mcneillis, V., Williamson, A., Joseph, J., Randhawa, P. S., Andrews, P. J., & Paleri, V. (2023) · European Archives of Oto-Rhino-Laryngology · doi:10.1007/s00405-023-08381-3 · Cited by 43 · see citing works
Jowarder, M. I. (2023) · Indonesian Journal of Innovation and Applied Sciences (IJIAS) · doi:10.47540/ijias.v3i2.878 · Cited by 36 · see citing works
Anxiety about artificial intelligence from patient and doctor-physician
Li, W., & Liu, X. (2024) · Patient Education and Counseling · doi:10.1016/j.pec.2024.108619 · Cited by 42 · see citing works
Verghese, B. G., Iyer, C., Borse, T., Cooper, S., White, J., & Sheehy, R. M. (2025) · BMC Medical Education · doi:10.1186/s12909-025-07321-5 · Cited by 34 · see citing works
The Artificial Intelligence in Digital Radiology: Part 1: The Challenges, Acceptance and Consensus
Giansanti, D., & Basilio, F. D. (2022) · Healthcare · doi:10.3390/healthcare10030509 · Cited by 33 · see citing works
Rainey, C., O’Regan, T., Matthew, J., Skelton, E., Woznitza, N., Chu, K.-Y., Goodman, S., McConnell, J., Hughes, C., Bond, R., et al. (2022) · Journal of medical imaging and radiation sciences · doi:10.1016/j.jmir.2022.05.010 · Cited by 29 · see citing works
Digitalization in Medicine: Are German Medical Students Well Prepared for the Future?
Sorg, H., Ehlers, J. P., & Sorg, C. G. G. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19148308 · Cited by 29 · see citing works
Pedersen, M. R. V., Kusk, M. W., Lysdahlgaard, S., Mork-Knudsen, H., Malamateniou, C., & Jensen, J. (2024) · Radiography · doi:10.1016/j.radi.2024.02.020 · Cited by 25 · see citing works
Hassankhani, A., Amoukhteh, M., Valizadeh, P., Jannatdoust, P., Sabeghi, P., & Gholamrezanezhad, A. (2023) · Academic Radiology · doi:10.1016/j.acra.2023.05.024 · Cited by 25 · see citing works
Moglia, A., Georgiou, K. E., Cerveri, P., Mainardi, L. T., Satava, R. M., & Cuschieri, A. (2024) · Artificial Intelligence Review · doi:10.1007/s10462-024-10849-5 · Cited by 24 · see citing works
Neittaanmäki, N. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1517116 · Cited by 23 · see citing works
Tang, D., Li, C., Du, T., Jiang, H., Ma, D., Ma, Z., Grzegorzek, M., Jiang, T., & Sun, H. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108217 · Cited by 18 · see citing works
Factors influencing the choice of radiology as a medical specialty in Ireland
Lynch, T., Bockhold, S., & McNulty, J. P. (2022) · European Journal of Radiology · doi:10.1016/j.ejrad.2022.110297 · Cited by 16 · see citing works
Drukker, L. (2022) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.24869 · Cited by 16 · see citing works
Pawelczyk, J., Kraus, M., Eckl, L., Nehrer, S., Aurich, M. E., Izadpanah, K., Siebenlist, S., & Rupp, M. (2024) · Archives of Orthopaedic and Trauma Surgery · doi:10.1007/s00402-024-05408-0 · Cited by 17 · see citing works
Murugesan, A., Patel, S., Bhargava, P., & Cooke, E. A. (2022) · Current Problems in Diagnostic Radiology · doi:10.1067/j.cpradiol.2022.07.002 · Cited by 15 · see citing works
Application of artificial intelligence in medical education: A meta-ethnographic synthesis
Li, W., Shi, H.-Y., Chen, X.-L., Lan, J., Rehman, A.-U., Ge, M., Shen, L.-T., Hu, F., Jia, Y., Li, X., et al. (2024) · Medical Teacher · doi:10.1080/0142159x.2024.2418936 · Cited by 15 · see citing works
Almarzouki, A. F., Alem, A., Shrourou, F., Kaki, S., Khushi, M., Mutawakkil, A., Bamabad, M., Fakharani, N., Alshehri, M., & Binibrahim, M. (2025) · BMC Medical Education · doi:10.1186/s12909-024-06446-3 · Cited by 14 · see citing works
Liu, D. S., Abu-Shaban, K., Halabi, S. S., & Cook, T. S. (2023) · JMIR Medical Education · doi:10.2196/43415 · Cited by 14 · see citing works
Dear Medical Students - Artificial Intelligence is Not Taking Away a Radiologist's Job
Murugesan, A., Patel, S., Viswanathan, V. S., Bhargava, P., & Faraji, N. (2022) · Current Problems in Diagnostic Radiology · doi:10.1067/j.cpradiol.2022.08.001 · Cited by 12 · see citing works
When everyone is talking about AI: The development of fear of missing out on AI scale
Deng, F., Zhang, Z., Lin, Y., Xiaoping, M., & Zhang, Y. (2025) · Telematics and Informatics · doi:10.1016/j.tele.2025.102283 · Cited by 14 · see citing works
Neitzel, E., vanSonnenberg, E., Lynch, K., Irwin, C., Shah-Patel, L. R., & Mamlouk, M. D. (2023) · Academic Radiology · doi:10.1016/j.acra.2023.09.025 · Cited by 11 · see citing works
Mengi, A., Singh, R. P., Mengi, N., Kalgotra, S., & Singh, A. (2024) · Journal of Oral Biology and Craniofacial Research · doi:10.1016/j.jobcr.2024.06.004 · Cited by 11 · see citing works
TIP FAKÜLTESİ ÖĞRENCİLERİNİN TIBBİ YAPAY ZEKA HAZIR BULUNUŞLULUĞUNUN İNCELENMESİ
Gencer, K., & Gencer, G. (2024) · Kocatepe tıp dergisi. · doi:10.18229/kocatepetip.1295779 · Cited by 9 · see citing works
The Future of Academic Neuroradiology: Challenges, Opportunities, and Way Forward
Malhotra, A. (2024) · American Journal of Neuroradiology · doi:10.3174/ajnr.a8539 · Cited by 9 · see citing works
Xie, H., Dai, X., Xie, J., Lei, S., Zeng, J., Yang, J., & Zhou, Y. (2025) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s538723 · Cited by 7 · see citing works
Alamer, A. (2022) · Current Medical Imaging Formerly Current Medical Imaging Reviews · doi:10.2174/1573405618666220907111422 · Cited by 7 · see citing works
Teaching Artificial Intelligence Literacy: A Challenge in the Education of Radiology Residents
Mello-Thoms, C. R. (2023) · Academic Radiology · doi:10.1016/j.acra.2023.04.035 · Cited by 6 · see citing works
Hameed, M. Y., Al-Hindi, L., Ali, S., Jensen, H., & Shoults, C. C. (2023) · Current problems in diagnostic radiology · doi:10.1067/j.cpradiol.2023.04.003 · Cited by 4 · see citing works
Udam, N. G., Obaje, P. A., Emegoakor, A. C., Edache, E. L., Obaje, E. O., Oladosu, A. O., AbdulKadir, A., Nneji, D. T., Odusola, O. D., Ofem, A. C., et al. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08067-w · Cited by 4 · see citing works
KOÇ, A., Ataş, A. E., Yosunkaya, Ş., & Vatansev, H. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1761025 · Cited by 5 · see citing works
Hakami, K., Alameer, M., Jaawna, E., Sudi, A., Bahkali, B. I., Mohammed, A., Hakami, A. A., Mahfouz, M. S., Alhazmi, A., & Dhayihi, T. (2023) · Cureus · doi:10.7759/cureus.41840 · Cited by 5 · see citing works
Almuhanna, A., Almohsen, D. S., Alsultan, D. H., Alhuraish, D., AlRatrout, F., Alzanadi, R. H., & Abbas, R. (2025) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205251358005 · Cited by 3 · see citing works
Will Artificial Intelligence Get in the Way of Achieving Gender Equality?Preprint
Isaksson, S., Buitrago, C. F., & Carvajal, D. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4758197 · Cited by 3 · see citing works
Invest in the future: “Hands-on Radiology” summer school
Segger, L., Marth, A. A., Gosch, V., Oppenheimer, J., Lüken, S., Bierbrauer, A., Nilssen, M. S., Jahn, M., Hamm, B. K., Lerchbaumer, M. H., et al. (2023) · Insights into Imaging · doi:10.1186/s13244-023-01382-0 · Cited by 2 · see citing works
Pirocca, U., Vinchon, F., Bérégi, J.-P., Jacques, T., Delabrousse, É., Gouy, E., Rolland, F., Truong, L. N., Frajerman, A., Ohana, M., et al. (2023) · European Journal of Radiology · doi:10.1016/j.ejrad.2023.111115 · Cited by 2 · see citing works
Prospective Physicians’ Intention to Adopt Artificial Intelligence: A Configurational Perspective
Paré, G., Raymond, L., Castonguay, A., & Wagner, G. (2023) · Hawaii International Conference on System Sciences (HICSS) · doi:10.24251/hicss.2023.369 · Cited by 2 · see citing works
Chen, M., Zhang, B., Cai, Z., Seery, S., Mendez, M. J., Ali, N. M., Ren, R., Qiao, Y., Xue, P., & Jiang, Y. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4128867 · Cited by 2 · see citing works
Medical Education Learning Specialists in the Age of Artificial Intelligence
Hu, H. H., Wallace, D. D., & Boateng, B. A. (2025) · Cureus · doi:10.7759/cureus.88439 · Cited by 1 · see citing works
What drives Malaysian medical students’ specialty choices? Findings from the MMSCI study
Ser, G. T. Z., Teng, Z. S., Hong, W.-H., Teo, C. H., Aziz, Y. F. A., Vadivelu, J. S., Collaborative, T. M. M., Devan, J. N., Ong, N., Law, S. H., et al. (2025) · Human Resources for Health · doi:10.1186/s12960-025-01042-y · Cited by 1 · see citing works
Current Situation and Prospects of Education in Medical Imaging Artificial Intelligence
Zhang, X., Jiang, L. H., Liang, M., Guo, L., Xiao, Y., & Wang, Y. (2024) · Springer eBooks · doi:10.1007/978-981-99-8441-1_28
Filipek, K., Pisklak, A., Winiarska, N., Remiszewski, P., Łuczkiewicz, K., Wierzbiński, P., Barylski, M., Poliwczak, A. R., & Śliż, D. (2025) · BMC Medical Education · doi:10.1186/s12909-025-06886-5
Künstliche Intelligenz in der chirurgischen Weiterbildung
Deichsel, A., Oettl, F. C., Pawelczyk, J., Usov, L., & Haffer, H. P. H. (2025) · Die Unfallchirurgie · doi:10.1007/s00113-025-01558-x
Varughese, E., de Burg, J. E. V., Borgman, G., Seyidov, T., & Fletcher, R. (2026) · Medical Science Educator · doi:10.1007/s40670-025-02630-2
Alkahtany, S. M., Almalky, H. A., Albahouth, H. S., Almutairi, E. S., Alatyan, M. H., Almohaimede, A. A., Al-Maflehi, N. S., & Al‐Madi, E. M. (2026) · European Journal Of Dental Education · doi:10.1111/eje.70140
The Future of AI and Radiology Is Not as Simple as You Think
Benson, J. C. (2026) · Radiology · doi:10.1148/radiol.260838
Li, H., Zhang, Z., Yang, B., Liu, C., Sun, J., Zhou, J., & Cao, X. (2026) · BMC Nursing · doi:10.1186/s12912-026-05275-7
Zhang, J., & Ge, G. R. (2026) · Academic Radiology · doi:10.1016/j.acra.2026.08.095
- Authors
- Reeder, K., & Lee, H.
- Affiliations
- Quinnipiac University (US)
- University of Pennsylvania (US)
- Corresponding author
- Lee, Hwan
- Venue
- Clinical Imaging
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 81
- Pages
- 67-71
- ISSN
- 0899-7071 (ISSN-L)
- OpenAlex
- W3203379271
- Cited by
- 60
- References
- 15
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 13 · 2023: 16 · 2022: 13
- FWCI
- 5.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Clinical Imaging (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
- Social Sciences › Gender Studies › Diversity and Career in Medicine
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence, medical students, career interest, AI anxiety, radiology education, AI exposure, radiology workforce
- MeSH terms
- Artificial Intelligence, Humans, Surveys and Questionnaires, Radiography, Radiology, 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 ›
Are you an author, or do you see a problem with this page? Request a review
