Evaluation of Gemini 2.0 AI in Classifying Breast Lesion Status From Dynamic Contrast-Enhanced MRI: A Preliminary Study
Gemini 2.0 offers preliminary utility in breast lesion detection on DCE-MRI, particularly in identifying malignancy. However, its limited specificity and poor differentiation between lesion types underscore the need for continued development before clinical deployment.
Authors
- T. M. Praneeth Naidu (ORCID: https://orcid.org/0000-0002-7029-6308)
- Andrew Bouras (ORCID: https://orcid.org/0000-0002-7960-9358)
- Nasif Zaman (ORCID: https://orcid.org/0000-0003-0120-0939)
- Nitin Chetla (ORCID: https://orcid.org/0009-0003-3496-262X)
- Shivam Patel
- Harshita Kacham
- Vinisha Bonagiri
Institutions
- University of Nevada, Reno (US)
- Nova Southeastern University (US)
- Dr. NTR University of Health Sciences (IN)
- University of Virginia (US)
- Virginia Tech (US)
- Osmania University (IN)
Publication Details
- Journal
- Cureus
- Published
- 2025-10-08
- DOI
- https://doi.org/10.7759/cureus.94144
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00