SurvMamba: State Space Model with Multi-grained Multi-modal Interaction for Survival Prediction

arXiv:2404.08027v1 Announce Type: cross
Abstract: Multi-modal learning that combines pathological images with genomic data has significantly enhanced the accuracy of survival prediction. Nevertheless, existing methods have not fully utilized the inherent hierarchical structure within both whole slide images (WSIs) and transcriptomic data, from which better intra-modal representations and inter-modal integration could be derived. Moreover, many existing studies attempt to improve multi-modal representations through attention mechanisms, which inevitably lead to high complexity when processing high-dimensional WSIs and transcriptomic data. Recently, a …

abstract accuracy arxiv cs.ai cs.cv cs.lg data genomic genomic data hierarchical images modal multi-modal prediction q-bio.qm space state state space model survival type