Comparing faculty and artificial intelligence in grading ophthalmology residency applications

AI accurately predicts match outcomes and can be used as an adjunct aide to faculty review of applications to reduce the immense administrative workload and human bias.

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Publication Details

Journal
Academic Medicine
Published
2025-12-06
DOI
https://doi.org/10.1093/acamed/wvaf055
Primary Topic
Diversity and Career in Medicine
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparing faculty and artificial intelligence in grading ophthalmology residency applications

Jared Moon, Owen Sorensen, Priyam Mazumdar, Ilyas Iyoob et al.
Academic Medicine
Diversity and Career in Medicine
article

Comparing faculty and artificial intelligence in grading ophthalmology residency applications

Jared Moon, Owen Sorensen, Priyam Mazumdar, Ilyas Iyoob, Gene Kim
article en

Abstract

AI accurately predicts match outcomes and can be used as an adjunct aide to faculty review of applications to reduce the immense administrative workload and human bias.

Academic MedicineVol. 101(3)
University of Illinois Urbana-Champaign (US), The University of Texas at Austin (US)
Quality Education
Openalex Percentile: Top 15%
Diversity and Career in Medicine
DOISourceOpenAlex
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Comparing faculty and artificial intelligence in grading ophthalmology residency applications — Jared Moon, Owen Sorensen, et al. · Academic Medicine (2025) | TGRS Research Map | TGRS