We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Letters of recommendations and personal statements for rhinology fellowship: A deep learning linguistic analysis.
- Authors
Vasan, Vikram; Cheng, Christopher; Lerner, David K.; Signore, Anthony Del; Schaberg, Madeleine; Govindaraj, Satish; Iloreta, Alfred Marc
- Abstract
Our study aims to use natural language processing (NLP) and deep learning to evaluate general and linguistic category differences in Rhinology fellowship LORs and PSs between the genders of the applicant and between international medical graduates (IMGs) and US-trained candidates. 1 TABLE (a) Demographic distribution of the 56 Rhinology fellowship applicants (b) Word counts of different application components for Rhinology fellowship applicant gender and medical school training background. Keywords: application process; gender disparity; international medical graduate; letters of recommendation; personal statements; Rhinology fellowship match EN application process gender disparity international medical graduate letters of recommendation personal statements Rhinology fellowship match 1971 1973 3 09/27/23 20231001 NES 231001 INTRODUCTION The Rhinology fellowship match process is highly competitive and has seen a recent increase in interest levels over recent years.[[1], [3]] The Rhinology fellowship application includes several different components, including letters of recommendation (LORs) and personal statements (PSs).
- Subjects
NOSE; DEEP learning; LINGUISTIC analysis; NATURAL language processing
- Publication
International Forum of Allergy & Rhinology, 2023, Vol 13, Issue 10, p1971
- ISSN
2042-6976
- Publication type
Article
- DOI
10.1002/alr.23153