Article

DeMoP: A Language-Model-Guided Mixture-of-Experts Framework for Cancer Prognosis

2026-08-27

Abstract excerpt

Integrating heterogeneous clinical and molecular data for cancer prognosis remains challenging because their dimensionality, semantics and distributions differ across patients and cohorts. Here we present DeMoP, a language-model-guided mixture-of-experts framework that serializes structured patient profiles as natural-language sequences and learns adaptive prognostic representations from clinical variables, copy-n...

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Literature Corpus work: f9e8bba1-d490-50c3-b28d-05d112e41ee4
DOI: 10.64898/2026.08.24.746579

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