Breast cancer detection and classification via a robust deep learning approach

Abstract This work presents a leakage-controlled deep-learning framework for breast cancer classification using the CBIS-DDSM mammography archive. The proposed pipeline combines patient-level data partitioning before augmentation, a two-stage transfer-learning strategy based on ResNet50, and an Inte...

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Autors principals:	Magy Makram, Alber S. Aziz, Mary Monir Saeid, Mostafa Thabet Mohamed
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2026-07-01
Col·lecció:	Scientific Reports
Matèries:	Breast cancer classification Mammography CBIS-DDSM ResNet50 Inter-view attention fusion Transfer learning
Accés en línia:	https://doi.org/10.1038/s41598-026-62255-2
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