CMSwinKAN, a lightweight Swin-KAN hybrid with contrastive multi-scale fusion, reportedly outperforms pathology foundation models on neuroblastoma classification and achieves 100% WSI accuracy on a private dataset.
Pseudo-bag mixup augmen- tation for multiple instance learning-based whole slide image classification,
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Towards Accurate and Interpretable Neuroblastoma Diagnosis via Contrastive Multi-scale Pathological Image Analysis
CMSwinKAN, a lightweight Swin-KAN hybrid with contrastive multi-scale fusion, reportedly outperforms pathology foundation models on neuroblastoma classification and achieves 100% WSI accuracy on a private dataset.