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Article

Random forest-based modelling to detect biomarkers for prostate cancer progression

22 Oct 2019

Abstract excerpt

BACKGROUND: The clinical course of prostate cancer (PCa) is highly variable, demanding an individualized approach to therapy. Overtreatment of indolent PCa cases, which likely do not progress to aggressive stages, may be associated with severe side effects and considerable costs. These could be avoided by utilizing robust prognostic markers to guide treatment decisions. RESULTS: We present a random forest-based...

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PMID: 31640781
DOI: 10.1186/s13148-019-0736-8

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