Class Visualizations and Activation Atlases for Enhancing Interpretability in Deep Learning-Based Computational Pathology

arXiv:2603.07170v2 Announce Type: replace Abstract: The rapid adoption of transformer-based models in computational pathology has enabled prediction of molecular and clinical biomarkers from H&E whole-slide images, yet interpretability has not kept pace with model complexity. ...

🔗 Read more: https://arxiv.org/abs/2603.07170

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