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Random survival forests for competing risks.


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.

SUBMITTER: Ishwaran H 

PROVIDER: S-EPMC4173102 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Random survival forests for competing risks.

Ishwaran Hemant H   Gerds Thomas A TA   Kogalur Udaya B UB   Moore Richard D RD   Gange Stephen J SJ   Lau Bryan M BM  

Biostatistics (Oxford, England) 20140411 4


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. ...[more]

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