Enhancing WSI image classification with graph convolutional neural networks and model uncertainty modeling

Abstract Background The primary research question addresses whether integrating Graph Convolutional Neural Networks with model uncertainty modeling can improve the accuracy and robustness of Whole Slide Imaging (WSI) classifications in pathology. Methods This study employed a novel framework combini...

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Autori principali:	Chaoyue Liu, Yongxiang Cheng, Ting Li, Yanke Hao, Qiang Zhang
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2026-01-01
Serie:	BMC Medical Imaging
Soggetti:	Whole Slide Imaging Graph convolutional neural networks Model uncertainty modeling Computational pathology Deep learning Spinal infection classification
Accesso online:	https://doi.org/10.1186/s12880-025-02130-0
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