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

Natural Language Processing (706) Machine Learning (1501) Electronic Health Records (1068) Clinical Informatics (1050) Clinical Information and Decision Making (1434) Ontologies, Classifications, and Coding (243) Secondary Use of Clinical Data for Research and Surveillance (375)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23101, first published .
Incorporating Domain Knowledge Into Language Models by Using Graph Convolutional Networks for Assessing Semantic Textual Similarity: Model Development and Performance Comparison

Incorporating Domain Knowledge Into Language Models by Using Graph Convolutional Networks for Assessing Semantic Textual Similarity: Model Development and Performance Comparison

Incorporating Domain Knowledge Into Language Models by Using Graph Convolutional Networks for Assessing Semantic Textual Similarity: Model Development and Performance Comparison

Authors of this article:

David Chang1 Author Orcid Image ;   Eric Lin2 Author Orcid Image ;   Cynthia Brandt1, 3, 4 Author Orcid Image ;   Richard Andrew Taylor1, 3 Author Orcid Image
Article Authors Cited by (5) Tweetations (6) Metrics

David Chang   1 , DPhil ;   Eric Lin   2 , MD ;   Cynthia Brandt   1, 3, 4 , MPH, MD ;   Richard Andrew Taylor   1, 3 , MD

1 Yale Center for Medical Informatics, Yale University, New Haven, CT, United States

2 Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States

3 Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT, United States

4 West Haven Campus, Veterans Affairs Connecticut Healthcare System, West Haven, CT, United States

Corresponding Author:

  • Richard Andrew Taylor, MD
  • Yale Center for Medical Informatics
  • Yale University
  • Suite 501
  • 300 George St
  • New Haven, CT
  • United States
  • Phone: 1 2037854058
  • Email: richard.taylor@yale.edu