A weakly supervised pre-training scheme that propagates bag labels to patches improves downstream MIL classification and survival prediction on WSI datasets, but the comparison baselines are not trained on the same target data.
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SimMIL: A Universal Weakly Supervised Pre-Training Framework for Multi-Instance Learning in Whole Slide Pathology Images
A weakly supervised pre-training scheme that propagates bag labels to patches improves downstream MIL classification and survival prediction on WSI datasets, but the comparison baselines are not trained on the same target data.