The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology
The episode discusses the paper "The Next Layer," which introduces EAGLE-Net for computational pathology. The team addresses the gap between isolated patch analysis and understanding global tissue context. They detail how EAGLE-Net uses structure-preserving encoding, neighborhood-aware loss, and background suppression to improve survival prediction and classification accuracy across various cancer types.