[Transformation of free-text radiology reports into structured data].

Journal: Radiologie (Heidelberg, Germany)

Published Date: Feb 11, 2025

Abstract

BACKGROUND: The rapid development of large language models (LLMs) opens up new possibilities for the automated processing of medical texts. Transforming unstructured radiology reports into structured data is crucial for efficient use in clinical decision support systems, research, and improving patient care.

Authors

Markus M Graf
Keno K Bressem

School of Medicine and Health, Institute for Cardiovascular Radiology and Nuclear Medicine, German Heart Center Munich, TUM University Hospital, Technical University of Munich, Munich, Germany.
Lisa C Adams

School of Medicine and Health, Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, TUM University Hospital, Technical University of Munich, Munich, Germany.

Keywords

Deep Learning Humans Machine Learning Natural Language Processing Neural Networks, Computer Radiology Information Systems

External Resources

View on PubMed Access via DOI PubMed (39934245)

[Transformation of free-text radiology reports into structured data].

Abstract

Authors

Keywords

External Resources

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