Tatjana Kiseļova

A novel multiomics machine learning signature identifies rapid progression in clinically low risk prostate cancer

Abstract Risk stratification in primary prostate cancer remains heavily reliant on clinicopathological criteria that frequently miss the heterogeneity underlying early aggressive disease. We present a novel machine learning non-linear prognostic framework encoding somatic copy-nu...