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.
A foundation model for clinical-grade computational pathology and rare cancers detection.Nature medicine, 30(10):2924–2935
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A masked-diffusion pretrained convolutional model outperforms ViT pathology foundation models on cell-level dense prediction tasks in histology.
citing papers explorer
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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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Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction
A masked-diffusion pretrained convolutional model outperforms ViT pathology foundation models on cell-level dense prediction tasks in histology.