Published on in Vol 9 , No 2 (2021) :February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22795, first published .
Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study

Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study

Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study

Klaus Kades 1, 2 * , MSc ;   Jan Sellner 1, 3 * , MSc ;   Gregor Koehler 1 , MSc ;   Peter M Full 1, 4 , BSc ;   T Y Emmy Lai 1, 5 , MSc ;   Jens Kleesiek 1, 2, 3, 6 * , MD, PhD ;   Klaus H Maier-Hein 1, 2, 3, 4 * , PhD

1 German Cancer Research Center (DKFZ) , Heidelberg , DE

2 Partner Site Heidelberg , German Cancer Consortium (DKTK) , Heidelberg , DE

3 Helmholtz Information and Data Science School for Health , Karlsruhe/Heidelberg , DE

4 Heidelberg University , Heidelberg , DE

5 Hochschule Mannheim , University of Applied Sciences , Mannheim , DE

6 Institute for Artificial Intelligence in Medicine (IKIM) , University Medicine Essen , Essen , DE

*these authors contributed equally

Corresponding Author:

  • Klaus Kades, MSc
  • German Cancer Research Center (DKFZ)
  • Im Neuenheimer Feld 280
  • Heidelberg
  • DE
  • Phone: 49 6221420
  • Email: k.kades@dkfz.de