Automated Radiology Report Labeling in Chest X-Ray Pathologies: Development and Evaluation of a Large Language Model Framework.
Journal:
JMIR medical informatics
PMID:
40153539
Abstract
BACKGROUND: Labeling unstructured radiology reports is crucial for creating structured datasets that facilitate downstream tasks, such as training large-scale medical imaging models. Current approaches typically rely on Bidirectional Encoder Representations from Transformers (BERT)-based methods or manual expert annotations, which have limitations in terms of scalability and performance.