Random Forests (Breiman 2001) (RF) are a fully non-parametric statistical method requiring no distributional assumptions on covariate relation to the response. RF are a robust, nonlinear technique that optimizes predictive accuracy by fitting an ensemble of trees to stabilize model estimates. Random Forests for survival (Ishwaran and Kogalur 2007; Ishwaran, Kogalur, Blackstone, and Lauer 2008) ...

We prove uniform consistency of Random Survival Forests (RSF), a newly introduced forest ensemble learner for analysis of right-censored survival data. Consistency is proven under general splitting rules, bootstrapping, and random selection of variables-that is, under true implementation of the methodology. Under this setting we show that the forest ensemble survival function converges uniforml...

Background and Objectives: In survival analysis, using the Cox model to determine the effective factors requires the assumptions whose failure of leads to biased results. The aim of this paper was to determine the factors affecting the survival of metastatic gastric cancer patients using the non-parametric method of Randomized Survival Forest (RSF) model and to compare its result with the Cox m...

BACKGROUND Random survival forest (RSF) models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (...

BACKGROUND Death is uncommon in thyroid cancer patients, and the factors important in predicting survival remain inadequately studied. The objective of this study was to assess prognostic effects of patient, tumor, and treatment factors and to determine prognostic groups for thyroid cancer survival. METHODS Using data from the Surveillance, Epidemiology, and End Results Program (SEER), we eva...

The Darwinian concept of evolution provides a usef3 theoretical construct to consider the ongoing development of forest management and forest operations. For example, changing environments, “survival of the fittest”, and random mutation are processes, which have analogs within the forestry arena. The success and survival of any forest operations technology is determined by how well it meets the...