ArticleAcademic medicine : journal of the Association of American Medical Colleges2025
Artificial Intelligence Meets Holistic Review: Promises and Pitfalls of Automating the Medical Education Admissions Process.
Article in Academic medicine : journal of the Association of American Medical Colleges, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- The hidden patterns of alignment: exploring variability between generative AI and human.Medical education online · 2026Article
- Artificial Intelligence in Psychiatric Graduate Medical Education.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
- Leveraging design thinking to tackle contemporary admissions challenges in health professions education.PloS one · 2026Article
- DeepSeek for healthcare: do no harm?AI and ethics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
abstractHolistic review has been widely adopted in medical education as a means of promoting equity in the application process and diversity in the medical workforce. Artificial intelligence (AI) is a rapidly emerging technology already having an impact on the medical school and residency application process as students and faculty alike increasingly turn to AI tools to automate some steps in the preparation and evaluation of application materials. While AI may have the potential to improve the holistic admissions process by increasing efficiency and adding some measure of standardization among reviewers, the authors caution that this promise does not come without certain pitfalls. AI models may introduce new sources of bias and amplify existing ones, which, when combined with a lack of transparency regarding their use in the admissions process, may perpetuate the very inequities that holistic review seeks to minimize. The authors call for the medical education community to establish clear regulations to govern the acceptable use of AI in the admissions process and for a principled adoption of AI tools in a way that is sustainable for applicants and reviewers in the future.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.