Utilizing GPT-4o with context-based approaches for improved query of ACR RADS guidelines
Incorporating contextual information such as guideline documents substantially improves the accuracy of GPT-4o in answering ACR RADS-related questions.
Authors
- Daniel Kuetting (ORCID: https://orcid.org/0000-0001-6520-1020)
- Julian Alexander Luetkens (ORCID: https://orcid.org/0000-0002-7715-4636)
- Dmitrij Kravchenko (ORCID: https://orcid.org/0000-0003-0331-2045)
- Tatjana Dell (ORCID: https://orcid.org/0000-0002-2835-8560)
- Claus Christian Pieper (ORCID: https://orcid.org/0000-0002-0893-1200)
- Sebastian Nowak (ORCID: https://orcid.org/0000-0001-5175-5559)
- Narine Mesropyan (ORCID: https://orcid.org/0000-0002-5871-3965)
- Alexander Isaak (ORCID: https://orcid.org/0000-0003-2016-6166)
- Alois M. Sprinkart (ORCID: https://orcid.org/0000-0002-1435-9562)
- Babak Salam
- Joseph Sieber
Institutions
- University Hospital Bonn (DE)
Publication Details
- Journal
- European Journal of Radiology
- Published
- 2026-03-16
- DOI
- https://doi.org/10.1016/j.ejrad.2026.112807
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00