Advancing Radiology Education with Artificial Intelligence: Curriculum Planning, Implementation, and Evaluation
Artificial intelligence can be applied across radiology education to enhance curriculum development and delivery through data-driven needs assessment, content and assessment generation, personalized learning, and program evaluation and management.
Authors
- Farshad Shahkarami (ORCID: https://orcid.org/0009-0004-0429-1914)
- Bradley J. Erickson (ORCID: https://orcid.org/0000-0001-7926-6095)
- Hillary W. Garner (ORCID: https://orcid.org/0000-0002-6699-9692)
- Mahan Mathur (ORCID: https://orcid.org/0000-0002-0081-865X)
- Pouria Rouzrokh (ORCID: https://orcid.org/0000-0003-4664-0751)
- Mahtab Amini (ORCID: https://orcid.org/0009-0002-9236-8576)
- Parsa Rouzrokh (ORCID: https://orcid.org/0009-0004-5625-9756)
- Bardia Khosravi
Institutions
- Jacksonville College (US)
- Yale University (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
- Tehran University of Medical Sciences (IR)
Publication Details
- Journal
- Radiographics
- Published
- 2026-07-30
- DOI
- https://doi.org/10.1148/rg.250198
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute on Aging
- National Institute on Minority Health and Health Disparities