Literature DB >> 24728979

Random survival forests for competing risks.

Hemant Ishwaran1, Thomas A Gerds2, Udaya B Kogalur3, Richard D Moore4, Stephen J Gange5, Bryan M Lau5.   

Abstract

We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection in high-dimensional problems and in settings such as HIV/AIDS that involve many competing risks.
© The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  AIDS; Brier score; C-index; Competing risks; Cumulative incidence function; Ensemble

Mesh：

Year:  2014        PMID： 24728979      PMCID： PMC4173102          DOI： 10.1093/biostatistics/kxu010

Source DB:  PubMed          Journal:  Biostatistics        ISSN： 1465-4644            Impact factor:   5.899


  7 in total

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