LiteMIL: a computationally efficient cross-attention multiple instance learning for cancer subtyping on whole-slide images
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Purpose: Accurate cancer subtyping is essential for precision medicine but challenged by the computational demands of gigapixel whole-slide images (WSIs). Although transformer-based multiple instance learning (MIL) methods achiev... ...
