The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
On Artificial Intelligence and Deep Learning Within Medical Education
Abstract
The methodology of deep learning, a component of machine learning and artificial intelligence, is introduced. The opportunity for this technology to automate some aspects of medical practice is reviewed. Finally, a discussion is provided on the integration of concepts from deep learning into medical education.
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Among the 6 articles mentioning plans for curricular change, there is no indication of published articles following up on those plans.
“Of the 6 articles mentioning plans for curricular change, there is no indication of published articles following up on these plans.38,44,50,51”
From Educating Future Physicians in Artificial Intelligence (AI): An Integrative Review and Proposed Changes (2021) · cites this paper as [44]
Citations
Cites
The perceptron: A probabilistic model for information storage and organization in the brain.
Rosenblatt, F. (1958) · Psychological Review · doi:10.1037/h0042519 · Cited by 12,280
Chan, K. S., & Zary, N. (2019) · JMIR Medical Education · doi:10.2196/13930 · Cited by 877 · cited 1×
“11,12 It is unlikely that most clinicians will need expertise in the methodology of DL, but they likely should understand the fundamentals of how it works, to appreciate opportunities for its use, as well as to recognize its limitations to translate its meaning when interacting with other health…”
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Flagged first, then by citations
Research works printed but not linked: 10
- Warburton, 2003, Deep learning and education for sustainability., Int J Sustainability Higher Educ, 4, 44, 10.1108/14676370310455332 · DOI
- Carin, 2018, On deep learning for medical image analysis., JAMA, 320, 1192, 10.1001/jama.2018.13316 · DOI
- Esteva, 2017, Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks., Nature, 546, 686, 10.1038/nature22985 · DOI
- Arcadu, 2019, Deep learning algorithm predicts diabetic retinopathy progression in individual patients., NPJ Digit Med, 2, 92, 10.1038/s41746-019-0172-3 · DOI · Paper page
- Elliott Range, 2020, Application of a machine learning algorithm to predict malignancy in thyroid cytopathology., Cancer Cytopathol, 128, 287, 10.1002/cncy.22238 · DOI
- Saba, 2019, The present and future of deep learning in radiology., Euro J Radiol, 114, 14, 10.1016/j.ejrad.2019.02.038 · DOI · Paper page
- Garcia-Garcia, 2018, A survey on deep learning techniques for image and video semantic segmentation., Appl Soft Comput, 70, 41, 10.1016/j.asoc.2018.05.018 · DOI
- Kolachalama, 2018, Machine learning and medical education., NPJ Digit Med, 1, 54, 10.1038/s41746-018-0061-1 · DOI · Paper page
- Khalid, 2020, Evaluation of deep learning models for identifying surgical actions and measuring performance., JAMA Netw Open, 3, e201664, 10.1001/jamanetworkopen.2020.1664 · DOI
- Paranjape, 2019, Introducing artificial intelligence training in medical education., JMIR Med Educ, 5, e16048, 10.2196/16048 · DOI · Paper page
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 679
Karaca, O., Çalışkan, S. A., & Demir, K. (2021) · BMC Medical Education · doi:10.1186/s12909-021-02546-6 · Cited by 377
Grunhut, J., Wyatt, A. T., & Marques, O. (2021) · Journal of Medical Education and Curricular Development · doi:10.1177/23821205211036836 · Cited by 161
“38,44,50,51 It is not fully understood what is preventing medical schools from implementing these changes.”
BackgroundMoodi Ghalibaf, A., Moghadasin, M., Emadzadeh, A., & Mastour, H. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04553-1 · Cited by 29
Mastour, H., Mirzaei, S., Sohrabi, S., & Toofaninejad, E. (2026) · BMC Medical Education · doi:10.1186/s12909-026-09630-9 · Cited by 3
“With roots tracing back to the late 1950s via artificial neural networks [3], AI has evolved into a field where machine learning (ML) and deep learning (DL) empower systems to perform tasks that mimic human learning and problem-solving [4, 5].”
Metadata
- Authors
- Carin, L.
- Affiliations
- Duke University (US)
- Corresponding author
- Carin, Lawrence
- ORCID
- Carin, Lawrence
- Venue
- Academic Medicine
- Publisher
- Oxford University Press (OUP)
- Published
- 2020-08-04
- Volume
- 95
- Issue
- 11S
- Pages
- S10-S11
- ISSN
- 1040-2446 (ISSN-L)
- OpenAlex
- W3047629609
- Cited by
- 56
- References
- 2
- Citations by year
- 2025: 6 · 2024: 12 · 2023: 18 · 2022: 6 · 2021: 11 · 2020: 3
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Academic Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Innovations in Medical Education
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- artificial intelligence, deep learning, medical education, machine learning
- MeSH terms
- Deep Learning, Artificial Intelligence, Education, Medical
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