SOURCE-LINKED INTELLIGENCE

MIST: Multimodal Survival Prediction with Genomic-Guided Histology Attention

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Multimodal survival models can combine complementary prognostic information from whole-slide images and genomic profiles, but effective fusion remains challenging amid external cohort shift and computational complexity. To address these challenges, we propose MIST, multimodal survival prediction with genomic-guided histology attention. MIST represents genomic features as tokens and allows them to query compact foundation-model-derived histology context tokens before survival prediction. This design enriches molecular information with histology context rather than merging separately encoded mod

Read original source ↗ Open in workspace

recordType

paper

region

Global