Article

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

2019-04-08

Abstract excerpt

The clinical course of prostate cancer (PCa) is highly variable, demanding an individualized approach to therapy and robust prognostic markers for treatment decisions. We present a random forest-based classification model to predict aggressive behaviour of PCa. DNA methylation changes between PCa cases with good or poor prognosis (discovery cohort with n=70) were used as input. The model was validated with data fr...

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Literature Corpus work: 577c1d49-8ac3-56f0-9560-42754ec5149b
DOI: 10.1101/602334

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