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Gustave Roussy, Cancer Data Science Unit, CentraleSupélec, Université Paris-Saclay, INSERM, IHU PRISM
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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.
