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

Journals

  1. Keszthelyi D, Gaudet-Blavignac C, Bjelogrlic M, Lovis C. Patient Information Summarization in Clinical Settings: Scoping Review. JMIR Medical Informatics 2023;11:e44639 View
  2. Miranda O, Fan P, Qi X, Wang H, Brannock M, Kosten T, Ryan N, Kirisci L, Wang L. DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health. Journal of Personalized Medicine 2024;14(1):94 View
  3. Chang E, Sung S. Use of SNOMED CT in Large Language Models: Scoping Review. JMIR Medical Informatics 2024;12:e62924 View

Books/Policy Documents

  1. Chernomorchenko P, Panchenko A, Nikishina I. Analysis of Images, Social Networks and Texts. View