Enhanced breast cancer diagnosis using modified InceptionNet-V3: a deep learning approach for ultrasound image classification
The achieved findings underscore the potential of the proposed approach in enhancing diagnostic precision and confirm the superiority of the modified InceptionV3 model in breast cancer classification tasks.
Authors
- Ahsan Rafiq (ORCID: https://orcid.org/0000-0001-9526-1032)
- Mohammed Saleh Ali Muthanna (ORCID: https://orcid.org/0000-0002-1165-7812)
- Ahmed Aziz (ORCID: https://orcid.org/0000-0003-1826-6248)
- Samia Allaoua Chelloug (ORCID: https://orcid.org/0000-0002-9711-0235)
- Abduljabbar S. Ba Mahel (ORCID: https://orcid.org/0009-0006-8453-6081)
- Rana Alnashwan (ORCID: https://orcid.org/0000-0003-4771-736X)
Institutions
- Princess Nourah bint Abdulrahman University (SA)
- Southern Federal University (RU)
- University of Electronic Science and Technology of China (CN)
- Benha University (EG)
- Tashkent State University of Economics (UZ)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2025-04-22
- DOI
- https://doi.org/10.3389/fphys.2025.1558001
- Citations
- 7
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 17.37