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  • 统计与管理学院2017年学术报告第43

     

    【主  题】Statistical Learning for Individualized Treatment Rules

    【报告人】Yufeng Liu, 教授

    University of North Carolina

    【时  间】 2017年06月20日(星期二)14:00-15:00

    【地  点】 上海财经大学统计与管理学院大楼1208室

    【摘  要】Due to heterogeneity of many chronic diseases, precise personalized medicine, also known as precision medicine, has drawn increasing attentions in the scientic community. One main goal of precision medicine is to develop the most effective tailored therapy for each individual patient. To that end, one needs to incorporate individual characteristics to detect a proper individual treatment rule, by which suitable decisions on treatment assignments can be made to optimize patients' clinical outcome. In this talk, I will present new statistical learning techniques which directly target the optimal individual treatment rule. Both binary and multi-arm treatments are considered. Theoretical and numerical comparisons with several existing methods will be presented to demonstrate the effectiveness of the proposed methods.

    【邀请人】 冯兴东