Automatic structuring of radiology reports with on-premise open-source large language models - Woźnicki, Piotr; Laqua, Caroline; Fiku, Ina; Hekalo, Amar; Truhn, Daniel; Engelhardt, Sandy; Kather, Jakob Nikolas; Försch, Sebastian; D’Antonoli, Tugba Akinci; Pinto dos Santos, Daniel; Baeßler, Bettina; Laqua, Fabian Christopher (European radiology, 2025)
Structured reporting enhances comparability, readability, and content detail. Large language models (LLMs) could convert free text into structured data without disrupting radiologists’ reporting workflow. This study evaluated an on-premise, privacy-preserving LLM for automatically structuring free-text radiology reports.
Online veröffentlicht: 10. Oktober 2024
Gesehen am 03.04.2025