Predicting Metastatic Risk from Primary Cancer Tissue Architecture via Distance-Aware Spatial Modeling
Predicting distant metastasis from the digital H&E slides of the primary tumor is a critical yet challenging task in computational pathology. Multiple Instance Learning (MIL) approaches can attend to subdomains in whole slide images (WSIs) that harbor features of pre-metastatic cancer regions. However, conventional MIL...
Sandesh Pokhrel, Hamid Manoochehri, Beatrice S. Knudsen et al.
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