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

Theme Issue 2020:National NLP Clinical Challenges/Open Health Natural Language Processing 2019 Challenge Selected Papers (17) Machine Learning (1465) Natural Language Processing (693)

Published on in Vol 9, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23099, first published .
Predicting Semantic Similarity Between Clinical Sentence Pairs Using Transformer Models: Evaluation and Representational Analysis

Predicting Semantic Similarity Between Clinical Sentence Pairs Using Transformer Models: Evaluation and Representational Analysis

Predicting Semantic Similarity Between Clinical Sentence Pairs Using Transformer Models: Evaluation and Representational Analysis

Authors of this article:

Mark Ormerod1 Author Orcid Image ;   Jesús Martínez del Rincón1 Author Orcid Image ;   Barry Devereux1 Author Orcid Image
Article Authors Cited by (14) Tweetations (3) Metrics

Mark Ormerod   1 , BEng ;   Jesús Martínez del Rincón   1 , PhD ;   Barry Devereux   1 , PhD

1 Institute of Electronics, Communications & Information Technology, School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, United Kingdom

Corresponding Author:

  • Mark Ormerod, BEng
  • Institute of Electronics, Communications & Information Technology
  • School of Electronics, Electrical Engineering and Computer Science
  • Queen's University Belfast
  • Queen's Road
  • Queen's Island
  • Belfast, BT3 9DT
  • United Kingdom
  • Phone: 44 28 9097 1700
  • Email: mormerod01@qub.ac.uk