This paper is in the following e-collection/theme issue:

Artificial Intelligence (2129) Bioinformatics Methods and Algorithms (17) Tools, Programs and Algorithms (376) Validity, Reliability, and Bias (110) Clinical Informatics (1325) Clinical Information and Decision Making (1915)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68427, first published .
Enhancing Bidirectional Encoder Representations From Transformers (BERT) With Frame Semantics to Extract Clinically Relevant Information From German Mammography Reports: Algorithm Development and Validation

Enhancing Bidirectional Encoder Representations From Transformers (BERT) With Frame Semantics to Extract Clinically Relevant Information From German Mammography Reports: Algorithm Development and Validation

Enhancing Bidirectional Encoder Representations From Transformers (BERT) With Frame Semantics to Extract Clinically Relevant Information From German Mammography Reports: Algorithm Development and Validation

Authors of this article:

Daniel Reichenpfader1, 2 Author Orcid Image ;   Jonas Knupp3 Author Orcid Image ;   Sandro Urs von Däniken4 Author Orcid Image ;   Roberto Gaio5 Author Orcid Image ;   Fabio Dennstädt5 Author Orcid Image ;   Grazia Maria Cereghetti4 Author Orcid Image ;   André Sander6 Author Orcid Image ;   Hans Hiltbrunner4 Author Orcid Image ;   Knud Nairz4 Author Orcid Image ;   Kerstin Denecke1 Author Orcid Image
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Journals

  1. Dennstädt F, Fauser S, Cihoric N, Schmerder M, Lombardo P, Cereghetti G, von Däniken S, Minder T, Meyer J, Chiang L, Gaio R, Lerch L, Filchenko I, Reichenpfader D, Denecke K, Vojvodic C, Tatalovic I, Sander A, Hastings J, Aebersold D, von Tengg-Kobligk H, Nairz K. Implementing a Resource-Light and Low-Code Large Language Model System for Information Extraction from Mammography Reports: A Pilot Study. Journal of Imaging Informatics in Medicine 2025 View