Abstract: Highlights•We design GraphMamba to model long-range relations and spatial structure for WSI analysis.•GraphMamba couples graph and Mamba to enhance local tissue structure and global relations learning.•Intra-group graph Mamba explores the correlations among instances within each group.•Cross-group feature sampling extracts discriminative features across groups.•Inter-group graph Mamba boosts comprehensive bag representation for better prediction.
External IDs:dblp:journals/pr/ZhengYZJX25
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