SurvELM: An R package for high dimensional survival analysis with extreme learning machine

作者：

Highlights：

• A set of survival models to model high dimensional right-censored survival data are proposed.

• Our models are strong competitors to popular survival models such as RSF and Cox models.

• We provide a SurvELM R package and its online Shiny version.

摘要

•A set of survival models to model high dimensional right-censored survival data are proposed.•Our models are strong competitors to popular survival models such as RSF and Cox models.•We provide a SurvELM R package and its online Shiny version.

论文关键词：Survival ensemble,Extreme learning machines,Random forest,Censored data,Buckley–James transformation,Cox model

论文评审过程：Received 20 March 2018, Revised 30 May 2018, Accepted 2 July 2018, Available online 31 July 2018, Version of Record 12 September 2018.

论文官网地址：https://doi.org/10.1016/j.knosys.2018.07.009