Refining breast cancer classification: Customized attention integration approaches with dense and residual networks for enhanced detection
The DRAI architecture with TLE provides a robust, automated framework for breast cancer classification. Its exceptional accuracy lays a solid foundation for future advancements in automated diagnostics and offers a reliable method for aiding early breast cancer detection.
Authors
- Md Palash Uddin (ORCID: https://orcid.org/0000-0002-4429-6590)
- Anwar Hossain Efat
- S. M. Mahedy Hasan (ORCID: https://orcid.org/0009-0007-3915-396X)
- Mohammad Sakif Alam
Institutions
- Rajshahi University of Engineering and Technology (BD)
- Hajee Mohammad Danesh Science and Technology University (BD)
- International University of Business Agriculture and Technology (BD)
Publication Details
- Journal
- Digital Health
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1177/20552076241309947
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 4.96
Funders
- University of Engineering and Technology, Lahore
- Rajshahi University