Redesigning residency training with artificial intelligence: Implications for efficiency, quality, and workforce capacity
- DOI
- 10.1002/acm2.70875
- Published
- 2026-10-26
- Container
- Journal of Applied Clinical Medical Physics
- Publisher
- Wiley
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1002/acm2.70875,
title = {Redesigning residency training with artificial intelligence: Implications for efficiency, quality, and workforce capacity},
author = {Laurence E Court and Beth Beadle and Comron J Hassanzadeh and Skylar S Gay and Tucker J Netherton and Rebecca M Howell and Adam D Melancon},
year = {2026},
journal = {Journal of Applied Clinical Medical Physics},
doi = {10.1002/acm2.70875},
url = {https://doi.org/10.1002/acm2.70875}
}RIS
TY - JOUR TI - Redesigning residency training with artificial intelligence: Implications for efficiency, quality, and workforce capacity AU - Laurence E Court AU - Beth Beadle AU - Comron J Hassanzadeh AU - Skylar S Gay AU - Tucker J Netherton AU - Rebecca M Howell AU - Adam D Melancon PY - 2026 JO - Journal of Applied Clinical Medical Physics DO - 10.1002/acm2.70875 UR - https://doi.org/10.1002/acm2.70875 ER -
APA
Court, L. E., Beadle, B., Hassanzadeh, C. J., Gay, S. S., Netherton, T. J., Howell, R. M., & Melancon, A. D. (2026). Redesigning residency training with artificial intelligence: Implications for efficiency, quality, and workforce capacity. Journal of Applied Clinical Medical Physics. https://doi.org/10.1002/acm2.70875
Source records
- crossref · retrieved 2026-11-04T09:37:12.219Z