Hong Tian

MoESurv: a zero-sample and transferable survival prediction framework for rare cancers using mixture of experts

MoESurv, a zero-sample survival prediction framework that leverages a mix-ture-of-experts architecture to extract generalizable prognostic patterns from pan-cancer data, is proposed, demonstrating both clinical utility and biological interpretability.