arXiv AI
Sep 21

MIST: Multimodal Survival Prediction with Genomic-Guided Histology Attention

MIST is a multimodal survival prediction framework that fuses whole-slide images and genomic profiles by representing genomic features as tokens that query histology context tokens derived from a foundation model. The architecture enriches molecular information with histology context before survival prediction, avoiding late-stage merging of separately encoded modalities. Training incorporates discrete-time survival prediction, genomic feature masking, WSI dropout, and contrastive alignment, and demonstrates improved external C-index across colon, renal, lung, and glioblastoma cohorts compared to standard fusion baselines.

By Muhammet Sami Yavuz, Sabri Mustafa Kahya, Richard R. Chen, Jana Lipkova, Benedikt Wiestler