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SlideBank is a training-free framework for whole-slide image reasoning in pathology, using a persistent hierarchical evidence bank to improve consistency and reduce inference costs.
Introduces AdaSurvMamba, an adaptive framework for multimodal survival analysis that uses a dual-scale importance-aware reconstruction module and semantic aggregation scanning to improve integration of whole slide images and genomic profiles, achieving consistent gains across five TCGA cohorts.
This paper proposes TopoMamSurv, a Graph Mamba framework for whole-slide image survival analysis that uses topology-aware ordering to address Mamba's sensitivity to input order, and incorporates bidirectional Mamba and GCN for spatial context modeling.