Leveraging GPT-4 enables patient comprehension of radiology reports
RADiANT successfully enhances patient understanding and satisfaction through automated AI-driven report simplification, offering a scalable solution for patient-centred communication in clinical practice. This tool reduces clinician workload and supports informed patient decision-making, demonstrating the potential of LLMs beyond English-based healthcare contexts.
Authors
- Cornelis Verhoef (ORCID: https://orcid.org/0000-0001-9980-8613)
- Marianne de Vries (ORCID: https://orcid.org/0009-0009-9807-182X)
- Davy van de Sande (ORCID: https://orcid.org/0000-0003-4484-0995)
- Jacob J. Visser (ORCID: https://orcid.org/0000-0001-9935-2097)
- Michel E. van Genderen (ORCID: https://orcid.org/0000-0001-5668-3435)
- Denise E. Hilling (ORCID: https://orcid.org/0000-0002-5875-6164)
- Bram Eijlers
- Dirk J. Grünhagen (ORCID: https://orcid.org/0000-0001-8293-6002)
- Jan A.J.G. van den Brand (ORCID: https://orcid.org/0000-0002-1685-9886)
- Diederik A M P J Gommers (ORCID: https://orcid.org/0000-0001-6808-7702)
- M. H. Elise van Driel (ORCID: https://orcid.org/0009-0008-8710-094X)
- Fokko Smits
- Noa Blok
Institutions
- Erasmus MC (NL)
- Erasmus MC Cancer Institute (NL)
- Erasmus University Rotterdam (NL)
Publication Details
- Journal
- European Journal of Radiology
- Published
- 2025-04-11
- DOI
- https://doi.org/10.1016/j.ejrad.2025.112111
- Citations
- 11
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 27.29