南宫28加拿大软件

光华讲坛——社ng28南宫国际app名流与企业家论坛第6964期

主题：Successive classification learning for estimating quantile optimal treatment regimes基于递进分类学习的分位数最优治疗策略估计

主讲人：加拿大多伦多大学统计系 孔德含教授

主持人：统计与数据科学南宫28加拿大软件 林华珍教授

时间：6月23日16:00-17:00

地点：柳林校区弘远楼408ng28南宫国际app议室

主办单位：统计与数据科学南宫28加拿大软件 科研处

主讲人简介：

孔德含，多伦多大学统计学教授，美国统计协ng28南宫国际app（ASA）ng28南宫国际app士。研究方向包括脑图像，统计遗传和基因组学，函数型数据分析，因果推断，高维数据分析以及机器学习。研究成果发表在统计学国际顶级期刊JRSSB、JASA、Biometrika等，现任统计学期刊JASA副主编。

内容提要：

Quantile optimal treatment regimes (OTRs) aim to assign treatments that maximize a specified quantile of patients' outcomes. Compared to treatment regimes that target the mean outcomes, quantile OTRs offer fairer regimes when a lower quantile is selected, as it improves outcomes for vulnerable patients. In this paper, we propose a novel method for estimating quantile OTRs by reformulating the problem as a successive classification task, solvable via training a sequence of classifiers, each successive classifier built on the output of its predecessors. This reformulation enables us to leverage the powerful machine learning technique to enhance computational efficiency and handle complex decision boundaries. We also investigate the estimation of quantile OTRs when outcomes are discrete, a setting that has received limited attention in the literature. A key challenge is that direct extensions of existing methods to discrete outcomes often lead to inconsistency and ineffectiveness issues. To overcome this, we introduce a smoothing technique that maps discrete outcomes to continuous surrogates, enabling consistent and effective estimation. We provide theoretical guarantees to support our methodology, and demonstrate its superior performance through comprehensive simulation studies and real-data analysis.

悟空体育主要围绕分位数最优治疗策略的递进分类学习估计方法展开：分位数最优治疗策略旨在分配治疗以最大化患者结局的特定分位数；与以均值结局为目标的治疗策略相比，选择较低分位数时能提供更公平的方案，从而改善弱势患者的结局。本报告提出了一种新方法，将问题重新表述为递进分类任务，通过训练一系列分类器求解（每个后续分类器建立在前一个的输出之上），从而利用强大的机器学习技术提高计算效率并处理复杂决策边界。本报告还研究了结局为离散型（文献中关注较少的场景）时该策略的估计问题——直接推广现有方法往往导致不一致和无效。为此，引入平滑技术将离散结局映射为连续替代变量，实现一致有效估计。本报告提供了理论保证，并通过全面的模拟研究和真实数据分析展示了其优越性能。