MIST augments MIL projection layers with cross-modal gene-expression prototypes derived from spatial transcriptomics, yielding consistent gains on survival, subtyping, and biomarker tasks across 23 endpoints and 8 aggregators.
Transmil: Transformer based correlated multiple instance learning for whole slide image classification
2 Pith papers cite this work. Polarity classification is still indexing.
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SPAN is a hierarchical attention framework that constructs multi-scale pyramid representations from single-scale patch inputs for WSI classification and segmentation while preserving spatial relationships.
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Bridging the Modality Bottleneck in Pathology MIL through Virtual Molecular Staining
MIST augments MIL projection layers with cross-modal gene-expression prototypes derived from spatial transcriptomics, yielding consistent gains on survival, subtyping, and biomarker tasks across 23 endpoints and 8 aggregators.
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Learning Spatial-Preserving Hierarchical Representations for Digital Pathology
SPAN is a hierarchical attention framework that constructs multi-scale pyramid representations from single-scale patch inputs for WSI classification and segmentation while preserving spatial relationships.