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Using Machine Learning in Residency Applicant Screening
Academic Medicine Podcast
English - September 20, 2021 11:00 - 42 minutes - 82.1 MB - ★★★★ - 43 ratingsEducation Health & Fitness Medicine learners education faculty medicine physicians policy storytelling trainees Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Guest Jesse Burk-Rafel, MD, MRes, joins hosts Toni Gallo and Research in Medical Education (RIME) Committee member Mahan Kulasegaram, PhD, to discuss the development of a decision support tool that incorporates machine learning and the use of that tool in residency applicant screening. They also talk about the residency application process and potential ways that artificial or augmented intelligence (AI) might mitigate current challenges.
This is the first episode in a 3-part series of discussions with RIME authors about their medical education research and its implications for the field. Find the complete 2021 RIME supplement, which is free to read and download, at academicmedicine.org.
Read the article discussed in this episode: Development and Validation of a Machine-Learning-Based Decision Support Tool for Residency Applicant Screening and Review.
A transcript of this episode is available at academicmedicineblog.org.