Machine Learning for Predictive Analysis of Otolaryngology Residency Letters of Recommendation
Vikram Vasan,
Christopher P. Cheng,
David K. Lerner
et al.
Abstract:IntroductionLetters of recommendation (LORs) are a highly influential yet subjective and often enigmatic aspect of the residency application process. This study hypothesizes that LORs do contain valuable insights into applicants and can be used to predict outcomes. This pilot study utilizes natural language processing and machine learning (ML) models using LOR text to predict interview invitations for otolaryngology residency applicants.MethodsA total of 1642 LORs from the 2022–2023 application cycle were retr… Show more
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