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Aligning AI-generated reports with human pathologist attention boosts accuracy and interpretability, revealing the critical regions that inform cancer diagnoses.
Tile-level benchmarking can reliably shortlist top-performing models, potentially saving researchers significant time and resources in digital pathology.
State-of-the-art semi-supervised domain generalization (SSDG) methods crumble when faced with the real-world challenge of long-tailed class distributions, but IMaX offers a simple, effective fix.