AI added to the curriculum for doctors-to-be
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?
Several universities have started to create new medical curriculum, including a doctor-engineering, to answer the need of educating future medical leaders to the challenges of artificial intelligence in medicine.
“Several universities have started to create new medical curriculum, including a doctor-engineering (18), to answer the need of educating future medical leaders to the challenges of artificial intelligence in medicine (53).”
From Artificial Intelligence in Medicine: Today and Tomorrow (2020) · cites this paper as [53]
Among the 2 reports of implemented changes, there were no previous reported studies researching what students hope to gain from such changes or what methods would be most effective.
“Among the 2 reports of implemented changes, there were no previous reported studies researching what students hope to gain from such changes or what methods would be most effective.36,47”
From Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes (2021) · cites this paper as [36]
Currently, the state of AI in medical education is in its infancy and speculative stages.
“Currently, the state of AI in medical education is in its infancy and speculative stages [13-16].”
From Needs, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum (2022) · cites this paper as [13]
Cites
Still being checked.
Cited by
Sorted by citations
Artificial Intelligence in Medicine: Today and Tomorrow
Briganti, G., & Le Moine, O. (2020) · Frontiers in Medicine · doi:10.3389/fmed.2020.00027 · Cited by 743 · see citing works
Artificial intelligence literacy in higher and adult education: A scoping literature review
Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100101 · Cited by 658 · see citing works
Karaca, O., Çalışkan, S. A., & Demir, K. (2021) · BMC Medical Education · doi:10.1186/s12909-021-02546-6 · Cited by 377 · see citing works
Wang, X., Li, L., Tan, S. C., Yang, L., & Lei, J. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107798 · Cited by 336 · see citing works
Artificial intelligence education programs for health care professionals: Scoping review
Charow, R., Jeyakumar, T., Younus, S., Dolatabadi, E., Salhia, M., Al-Mouaswas, D., Anderson, M., Balakumar, S., Clare, M., Dhalla, A., et al. (2021) · JMIR Medical Education · doi:10.2196/31043 · Cited by 291 · see citing works
Grunhut, J., Wyatt, A. T., & Marques, O. (2021) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205211036836 · Cited by 161 · see citing works
“36,47 Similarly, among the 6 articles Grunhut et al with proposed changes to medical curriculum, there was no evidence-based method backing these proposals.”
BackgroundNeeds, Challenges, and Applications of Artificial Intelligence in Medical Education Curriculum
Grunhut, J., Marques, O., & Wyatt, A. T. M. (2022) · JMIR Medical Education · doi:10.2196/35587 · Cited by 166 · see citing works
Jha, N., Shankar, P. R., Al-Betar, M. A., Mukhia, R., Hada, K., & Palaian, S. (2022) · Advances in Medical Education and Practice · doi:10.2147/amep.s368519 · Cited by 143 · see citing works
Western Australian medical students’ attitudes towards artificial intelligence in healthcare
Stewart, J., Lu, J., Gahungu, N., Goudie, A., Fegan, P. G., Bennamoun, M., Sprivulis, P., & Dwivedi, G. (2023) · PLOS ONE · doi:10.1371/journal.pone.0290642 · Cited by 104 · see citing works
Ejaz, H., McGrath, H., Wong, B. L., Guise, A., Vercauteren, T., & Shapey, J. (2022) · DIGITAL HEALTH · doi:10.1177/20552076221089099 · Cited by 105 · see citing works
Schubert, T., Oosterlinck, T., Stevens, R. D., Maxwell, P. H., & van der Schaar, M. (2025) · eClinicalMedicine · doi:10.1016/j.eclinm.2024.102968 · Cited by 103 · see citing works
Liu, D. S., Sawyer, J., Luna, A., Aoun, J., Wang, J., Boachie, L., Halabi, S., & Joe, B. (2022) · JMIR Medical Education · doi:10.2196/38325 · Cited by 90 · see citing works
Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030
Aboalshamat, K. T., Alhuzali, R., Alalyani, A. J., Alsharif, S., Qadhi, H., Almatrafi, R. M., Ammash, D., & Alotaibi, S. (2022) · International Journal Of Pharmaceutical Research And Allied Sciences · doi:10.51847/nu8y6y6q1m · Cited by 68 · see citing works
Medical students need artificial intelligence and machine learning training
Pucchio, A., Eisenhauer, E. A., & Moraes, F. Y. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00846-2 · Cited by 61 · see citing works
Machine Learning Use for Prognostic Purposes in Multiple Sclerosis
Seccia, R., Romano, S., Salvetti, M., Crisanti, A., Palagi, L., & Grassi, F. (2021) · Life · doi:10.3390/life11020122 · Cited by 56 · see citing works
Mishra, A., Begley, S. L., Chen, A., Rob, M., Pelcher, I., Ward, M., & Schulder, M. (2023) · Neurosurgery · doi:10.1227/neu.0000000000002598 · Cited by 37 · see citing works
Mohajer-Bastami, A., Moin, S., Ahmad, S., Ahmed, A. R., Pouwels, S., Hajibandeh, S., Yang, W., Parmar, C. D., Kermansaravi, M., Khalil, M., et al. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1644041 · Cited by 70 · see citing works
Ziapour, A., Darabı, F., Janjani, P., Amani, M. A., Yıldırım, M., & Motevaseli, S. (2025) · BMC Medical Education · doi:10.1186/s12909-025-06852-1 · Cited by 26 · see citing works
Lamotkin, A. I., Иванович, К. Д., Анатольевич, Л. И., Livshitz, S. A., & Геннадьевна, П. Е. (2024) · FARMAKOEKONOMIKA Modern Pharmacoeconomics and Pharmacoepidemiology · doi:10.17749/2070-4909/farmakoekonomika.2024.254 · Cited by 20 · see citing works
Neittaanmäki, N. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1517116 · Cited by 23 · see citing works
Why Machine Learning Should Be Taught in Medical Schools
Nagy, M. R., Radakovich, N., & Nazha, A. (2022) · Medical Science Educator · doi:10.1007/s40670-022-01502-3 · Cited by 17 · see citing works
Arshad, M. F., Ahmed, F., Nonnis, F., Tamponi, C., Scala, A., & Varcasia, A. (2025) · Research in Veterinary Science · doi:10.1016/j.rvsc.2025.105776 · Cited by 16 · see citing works
York, T. J., Raj, S., Ashdown, T., & Jones, G. G. (2023) · BMC Medical Education · doi:10.1186/s12909-022-03976-6 · Cited by 16 · see citing works
The Impact of Artificial Intelligence (AI) and Robotics on Higher Education
Naqvi, G., Iqbal, F., Yousaf, J., & Tariq, R. (2023) · Journal of Management Practices Humanities and Social Sciences · doi:10.33152/jmphss-7.3.2 · Cited by 11 · see citing works
Evaluation of students’ digital literacy through an immersive university-high school collaboration
Bruckhaus, A., Bennett, A., Brawer-Cohen, M., Sinclair, M., Cruz, G. R.-D. L., Ragusa, G., & Duncan, D. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1429893 · Cited by 14 · see citing works
Sorte, S. R., Rawekar, A. R. A., Rathod, S. B., & Gandhi, N. S. (2025) · Journal of Education and Health Promotion · doi:10.4103/jehp.jehp_1030_24 · Cited by 6 · see citing works
Technology Basics for Telemedicine
Mitek, A. E. (2022) · Veterinary Clinics of North America Small Animal Practice · doi:10.1016/j.cvsm.2022.06.003 · Cited by 8 · see citing works
Interdisciplinary K-12 Control Education in Biomedical and Public Health Applications
Duncan, D., Garner, R., Bennett, A., Sinclair, M., Cruz, G. R.-D. L., & Pasik-Duncan, B. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.09.286 · Cited by 6 · see citing works
Using AI Platforms in AI Liberal Art Class
Song, J. (2023) · International Conference on Applied System Innovation · doi:10.1109/icasi57738.2023.10179567 · Cited by 5 · see citing works
Review on Artificial Intelligence in Medicine
Sharma, M., Chaudhary, P. R., Mudgal, A., Nautiyal, A., & Tangri, S. K. (2023) · Journal of Young Pharmacists · doi:10.5530/097515050514 · Cited by 5 · see citing works
Çankaya, A., & Fi̇li̇z, E. (2025) · Bandırma Onyedi Eylül Üniversitesi Sağlık Bilimleri ve Araştırmaları Dergisi · doi:10.46413/boneyusbad.1618422 · Cited by 5 · see citing works
El‐Kassas, M., Khalifa, R., Medhat, M. A., Yilmaz, Y. N., Tumi, A., Labidi, A., Almattooq, M., Sanai, F. M., Elbadry, M., Mohammed, M. O., et al. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1630831 · Cited by 4 · see citing works
Sendak, M., Gao, M. C., Ratliff, W., Whalen, K., Nichols, M., Futoma, J., & Balu, S. (2021) · Healthcare · doi:10.1016/j.hjdsi.2021.100555 · Cited by 4 · see citing works
Hawal, M. V., Simon, M., Husain, N. H. A., Al-Harrasi, S. K. R., & Al-Hinai, L. N. S. (2025) · Journal of Medical Education Development · doi:10.61882/edcj.18.3.14 · Cited by 3 · see citing works
AI Integration in Spanish Undergraduate Medical Education: National Cross-Sectional Study
Janeiro, A. E., Pereira, K. P., Mayol, J., Crespo, J., Carballo, F., Cabello, J. B., Ramos-Casals, M., Corbacho, B. P., & Turnés, J. (2026) · JMIR Medical Education · doi:10.2196/88511 · Cited by 3 · see citing works
Preparing Teachers for a ChatGPT-Influenced Workforce
Helvacı, İ. (2025) · Kastamonu Eğitim Dergisi · doi:10.24106/kefdergi.1683517 · Cited by 4 · see citing works
Midwifery Students’ Adaptation to Artificial Intelligence
Çelik, O. T., Uçar, T., Baransel, E. S., & Barut, S. (2026) · CIN Computers Informatics Nursing · doi:10.1097/cin.0000000000001374 · Cited by 2 · see citing works
Emara, H. T., Khafagy, M. A., Niazy, N. A., & Abdel-Salam, S. A. (2026) · BMC Medical Education · doi:10.1186/s12909-026-09677-8 · Cited by 2 · see citing works
Wojda, T. R., Hoffman, C., Kindler, K., Desai, A., & Visweswaran, S. (2024) · Artificial intelligence · doi:10.5772/intechopen.114907 · Cited by 2 · see citing works
Challenges of Artificial Intelligence in Medicine
Nasir, N., Al-Shabi, M. A., Al‐Yateem, N., Rahman, S. A., Subu, M. A., Hijazi, H. H. A., Ahmed, F. R., Dias, J. M., Marzouqi, A. M. A., Alkawaldeh, M. Y., et al. (2023) · IEEE Annual International Computer Software and Applications Conference (COMPSAC) · doi:10.1109/compsac57700.2023.00219 · Cited by 1 · see citing works
Galos, J., Friedman, A., Jamosmos, E., Allec, S. I., Blinzler, B. J., Grunenfelder, L. K., & Carberry, A. R. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--48057 · Cited by 1 · see citing works
Liu, D. S., Sawyer, J., Luna, A., Aoun, J., Wang, J., Boachie, L., Halabi, S. S., Cheng, X., & Joe, B. (2022) · doi:10.2196/preprints.38325
Molnár‐Gábor, F. (2023) · Collaborative bioethics · doi:10.1007/978-3-031-29451-8_23
Current challenges and ethical hurdles of integrating ChatGPT in radiology (Preprint)Preprint
Kumar, S. S. (2024) · doi:10.2196/preprints.58634
Han, H., Liu, W., Qing, H., & Li, X. (2024) · Advances in Educational Technology and Psychology · doi:10.23977/aetp.2024.080223
Training the future healthcare workforce for AI integration
Khan, S. M. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-33584-6.00020-7
Hayek, A. H. A., Charara, J., & Geryes, M. (2025) · International Conference on Control, Automation, and Instrumentation (IC2AI) · doi:10.1109/ic2ai62984.2025.10932200
A Narrative Review of Artificial Intelligence in Medical Education of Surgical Oncology
Hu, H., & Wu, Z. (2025) · Indian Journal of Surgery · doi:10.1007/s12262-025-04365-1
Digitaliseringsstrategier i praksis: Erfaringer fra tre danske universiteter
Hagood, D., Tamborg, A. L., Rossen, D. S., Dahl, M. R., Jensen, R. G. H., Knudsen, S. P., & Ørngreen, R. (2025) · Dansk Universitetspædagogisk Tidsskrift · doi:10.7146/dut.v20i38.148819
Development of digital learning tools for medical education with agile scrum methodology
Puncher, J., Karunananthan, S., Amrani, S., Archibald, D., Brunet, N., Forgues-Martel, S., Hajjar, A. E. J., Helmer‐Smith, M., Jolin‐Dahel, K., McCutcheon, T., et al. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08270-9
Karaca, O., Çalışkan, S. A., & Demir, K. (2021) · Figshare · doi:10.6084/m9.figshare.14059884
Karaca, O., Çalışkan, S. A., & Demir, K. (2021) · Figshare · doi:10.6084/m9.figshare.14059878
Karaca, O., Çalışkan, S. A., & Demir, K. (2021) · Figshare · doi:10.6084/m9.figshare.14059881
Bibi, M., Qasim, S., Raza, N., Khan, S., Zahra, R., & Fayaz, A. (2025) · The Healer Journal of Physiotherapy and Rehabilitation Sciences · doi:10.55735/k5rwtb76 · Cited by 1 · see citing works
Öğretmenleri ChatGPT'den Etkilenen İşgücüne Hazırlamak
Helvacı, İ. (2024) · DergiPark (Istanbul University)
Chen, X., Cai, S., & Yao, H. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14064-3
- Authors
- Brouillette, M.
- Corresponding author
- Brouillette, Monique
- Venue
- Nature Medicine
- Published
- 2019-12
- Volume
- 25
- Issue
- 12
- Pages
- 1808-1809
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W2994545764
- Cited by
- 56
- References
- 0
- Citations by year
- 2026: 4 · 2025: 15 · 2024: 8 · 2023: 9 · 2022: 10 · 2021: 9 · 2020: 1
- Type
- other
- Language
- en
- Open access
- closed
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- 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, medical education, course program, medical students, AI training
- MeSH terms
- Artificial Intelligence, Curriculum, Education, Medical, Humans
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