Evaluating text and visual diagnostic capabilities of large language models on questions related to the Breast Imaging Reporting and Data System Atlas 5th edition
This study demonstrates that while LLMs exhibit strong capabilities in text-based BI-RADS assessments, their visual diagnostic abilities are currently limited, necessitating further development and cautious application in clinical practice.
Authors
- Turay Cesur (ORCID: https://orcid.org/0000-0002-2726-8045)
- Yasin Celal Güneş (ORCID: https://orcid.org/0000-0001-7631-854X)
- Leman Günbey Karabekmez (ORCID: https://orcid.org/0000-0001-9862-0192)
- Eren Çamur (ORCID: https://orcid.org/0000-0002-8774-5800)
Institutions
- Ankara University (TR)
- State Hospital (GB)
- Türkiye Yüksek İhtisas Hastanesi (TR)
- Memorial Ankara Hospital (TR)
Publication Details
- Journal
- Diagnostic and Interventional Radiology
- Published
- 2024-09-09
- DOI
- https://doi.org/10.4274/dir.2024.242876
- Citations
- 13
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.52