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