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March 3, 2026
Open Access
Deep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings
ZB
Zsolt Bedőházi
Eötvös Loránd University
AB
András Biricz
Eötvös Loránd University
OK
Oz Kilim
Eötvös Loránd University
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Puntos clave
Stage prediction of breast cancer using deep learning shows high accuracy.
The model achieved an accuracy of 92%, indicating its potential effectiveness.
Assessment involved analyzing whole-slide images to derive significant predictive features.
Implications suggest that effective staging can happen even in resource-limited contexts.
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Deep-learning-based breast cancer stage prediction from H&E-stained whole-slide images in resource-constrained settings | Synapse
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Bedőházi et al. (Tue,) studied this question.
synapsesocial.com/papers/69a75ae8c6e9836116a215fb
https://doi.org/https://doi.org/10.1016/j.jpi.2026.100644