Extracting structured data from unstructured breast imaging reports with transformer-based models
Generative models, particularly BioGPT, offer a robust and scalable approach to automating the extraction of structured information from unstructured breast imaging reports. Their superior performance, combined with their ability to handle multiple tasks concurrently, highlights their potential to reduce the manual effort required for clinical data curation and to enable the efficient integration of imaging data into research and clinical workflows.
Authors
- Francisco Javier Díez (ORCID: https://orcid.org/0000-0001-9855-9248)
- Iñigo Bermejo Delgado
- Mikel Carrilero-Mardones (ORCID: https://orcid.org/0000-0003-4746-098X)
- Jorge Pérez-Martín
Institutions
- Universidad Nacional de Educación a Distancia (ES)
- Hasselt University (BE)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2026-01-09
- DOI
- https://doi.org/10.3389/fdgth.2025.1718330
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universidad Nacional de Educación a Distancia
- Universiteit Hasselt