Article

Clinically driven knowledge distillation for sparsifying high-dimensional multi-omics survival models

2022-02-10

Abstract excerpt

Recently, various methods have been proposed to integrate different heterogeneous high-dimensional genomic data sources to predict cancer survival, often in addition to widely available and highly predictive clinical data. Although clinical applications of survival models have high sparsity requirements, most state-of-the-art models do not naturally exhibit this sparsity, as they are based on random forests or dee...

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Literature Corpus work: 26a4d9b1-0601-5087-ac54-18975bd09e8a
DOI: 10.1101/2022.02.07.479388

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