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
Authors of this article:
Klaus
Kades
1, 2
;
Jan
Sellner
1, 3
;
Gregor
Koehler
1
;
Peter M
Full
1, 4
;
T Y Emmy
Lai
1, 5
;
Jens
Kleesiek
1, 2, 3, 6
;
Klaus H
Maier-Hein
1, 2, 3, 4
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