A patient-aware benchmarking of CNN and transformer architectures for breast cancer histopathology classification

IntroductionBreast cancer diagnosis using histopathological imaging remains a critical yet challenging task, requiring automated systems that generalize reliably across patients and varying imaging conditions. While deep learning models have shown strong performance, many prior studies employ image-...

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Bibliografiska uppgifter

Huvudupphov:	Veeram Priyanka, Modigari Narendra, Tharasi Dilleswar Rao
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Frontiers Media S.A. 2026-05-01
Serie:	Frontiers in Digital Health
Ämnen:	BreakHis dataset breast cancer histopathology computational pathology ConvNeXt deep learning benchmarking patient-aware cross-validation
Länkar:	https://www.frontiersin.org/articles/10.3389/fdgth.2026.1752938/full
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