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) Methods and Instruments in Medical Informatics (126) Clinical Informatics (1022) Ontologies, Classifications, and Coding (239) Electronic Health Records (1053) Machine Learning (1465) Natural Language Processing (692)

Published on in Vol 9, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27386, first published .
Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study

Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study

Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study

Authors of this article:

Qingyu Chen1 Author Orcid Image ;   Alex Rankine1, 2 Author Orcid Image ;   Yifan Peng1, 3 Author Orcid Image ;   Elaheh Aghaarabi1, 4 Author Orcid Image ;   Zhiyong Lu1 Author Orcid Image
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