"No negatives needed": weakly-supervised regression for interpretable tumor detection in whole-slide histopathology images

Marina D'Amato, Jeroen van der Laak, Francesco Ciompi

Accurate tumor detection in digital pathology whole-slide images (WSIs) is crucial for cancer diagnosis and treatment planning. Multiple Instance Learning (MIL) has emerged as a wi…