Tree-based Ensemble Methods For Individualized Treatment Rules.

ABSTRACT: There is a growing interest in development of statistical methods for personalized medicine or precision medicine, especially for deriving optimal individualized treatment rules (ITRs). An ITR recommends a patient to a treatment based on the patient's characteristics. The common parametric methods for deriving an optimal ITR, which model the clinical endpoint as a function of the patient's characteristics, can have suboptimal performance when the conditional mean model is misspecified. Recent methodology development has cast the problem of deriving optimal ITR under a weighted classification framework. Under this weighted classification framework, we develop a weighted random forests (W-RF) algorithm that derives an optimal ITR nonparametrically. In addition, with the W-RF algorithm, we pr

SUBMITTER: Zhu K 

PROVIDER: S-EPMC6812564 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature