数学科学学院

Tree-based Survival Models and Precision Medicine

来源:数学科学学院 发布时间:2018-12-05   825

题目:Tree-based Survival Models and Precision Medicine

报告人: Yifan Cui (宾夕法尼亚大学)

时间:2018.12.19(周三)下午 3:00

地点:紫金港校区管理学院行政楼14楼1417报告厅

摘要:

In the first part, we develop a theoretical framework for survival tree and forest models. We first investigate the method from the aspect of splitting rules. We show that existing approaches lead to a potentially biased estimation of the within-node survival and cause non-optimal selection of the splitting rules. Based on this observation, we develop an adaptive concentration bound result which quantifies the variance component for survival forest models. Furthermore, we show with two specific examples how these concentration bounds, combined with properly designed splitting rules, yield consistency results. In the second part, we focus on one application of survival trees in precision medicine which estimates individualized treatment rules nonparametrically under right censoring. We extend the outcome weighted learning to right censored data without requiring either inverse probability of censoring weighting or semi-parametric modeling of the censoring and failure times. To accomplish this, we take advantage of the tree-based approach to nonparametrically impute the survival time in two different ways. In simulation studies, our estimators demonstrate improved performance compared to existing methods. We also illustrate the proposed method on a phase III clinical trial of non-small cell lung.

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联系人:苏中根 (suzhonggen@zju.edu.cn)

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