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Open access Jul 2026

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.

Shuping Fang, Yu-Hang Wang, Mengyan Zhou et al. · 1 citation

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