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Open-source Large Language Models can Generate Labels from Radiology Reports for Training Convolutional Neural Networks
12
Zitationen
14
Autoren
2025
Jahr
Abstract
In this study, 7561 radiological reports of ankle X-ray images were automatically classified as describing an ankle fracture or not using a large language model. Using a dataset of 250 reports, the language model showed a classification accuracy of 92%. The generated labels were used to train an image classifier to detect ankle fractures on X-ray images. 15,896 images were used for training. The resulting model achieved an accuracy of 89.5% on a test dataset.
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Autoren
Institutionen
- Humboldt-Universität zu Berlin(DE)
- Freie Universität Berlin(DE)
- Charité - Universitätsmedizin Berlin(DE)
- University of Chicago(US)
- Harvard University(US)
- Massachusetts General Hospital(US)
- Athinoula A. Martinos Center for Biomedical Imaging(US)
- TUM Klinikum(DE)
- Centre Hospitalier Universitaire de Reims(FR)
- Hôpital Maison Blanche(FR)
- Université de Reims Champagne-Ardenne(FR)
- Deutsches Herzzentrum München(DE)