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)

Published on in Vol 8, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19735, first published .
Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models

Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models

Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models

Authors of this article:

Xi Yang1 Author Orcid Image ;   Xing He1 Author Orcid Image ;   Hansi Zhang1 Author Orcid Image ;   Yinghan Ma1 Author Orcid Image ;   Jiang Bian1 Author Orcid Image ;   Yonghui Wu1 Author Orcid Image
Article Authors Cited by (30) Tweetations (3) Metrics

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  19. Celikten T, Onan A. Exploring Text Similarity in Human and AI-Generated Scientific Abstracts: A Comprehensive Analysis. IEEE Access 2025;13:74313 View
  20. Kang S, Park H, Taira R, Kim H. Detecting Redundant Health Survey Questions by Using Language-Agnostic Bidirectional Encoder Representations From Transformers Sentence Embedding: Algorithm Development Study. JMIR Medical Informatics 2025;13:e71687 View

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