This paper is in the following e-collection/theme issue:

Natural Language Processing (706) Advanced Data Analytics in eHealth (142) AI Language Models in Health Care (61) Machine Learning (1501) Decision Support for Health Professionals (1210)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60272, first published .
Enhancing Bias Assessment for Complex Term Groups in Language Embedding Models: Quantitative Comparison of Methods

Enhancing Bias Assessment for Complex Term Groups in Language Embedding Models: Quantitative Comparison of Methods

Enhancing Bias Assessment for Complex Term Groups in Language Embedding Models: Quantitative Comparison of Methods

Authors of this article:

Magnus Gray1 Author Orcid Image ;   Mariofanna Milanova2 Author Orcid Image ;   Leihong Wu1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Magnus Gray   1 , MS ;   Mariofanna Milanova   2 , MSc, PhD ;   Leihong Wu   1 , PhD

1 Division of Bioinformatics & Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, United States

2 Department of Computer Science, Donaghey College of Science, Technology, Engineering, and Mathematics, University of Arkansas at Little Rock, Little Rock, AR, United States

Corresponding Author:

  • Leihong Wu, PhD
  • Division of Bioinformatics & Biostatistics
  • National Center for Toxicological Research
  • US Food and Drug Administration
  • 3900 NCTR Rd
  • Jefferson, AR, 72079
  • United States
  • Phone: 1 8705437121
  • Email: leihong.wu@fda.hhs.gov