A novel algorithm to reduce bias and improve the quality and diversity of residency interviewees.

Chrystal O LauAdam B JohnsonAbby R NolderDeanne KingGraham M Strub

Published in: Laryngoscope investigative otolaryngology (2022)

Traditional methods of scoring and inviting otolaryngology residency applicants can be confounded by regional and inter-rater biases. Employing a geographic distribution algorithm improves the quality and diversity of invited applicants, eliminates bias, and maintains the representation of underrepresented minority applicants.

Keyphrases

machine learning
deep learning
neural network
quality improvement
medical students