Reliable Breast Cancer Diagnostic System Using Uncertainty-Guided Multiple Instance Learning for Weakly Localized Histopathology Classification
Breast cancer diagnosis from histopathology images requires reliable and interpretable automated analysis. However, existing weakly supervised and multiple instance learning (MIL) approaches often overlook predictive uncertainty and tend to produce overconfident decisions in ambiguous cases, thereby limiting the reliab...