title: Recent development on statistical methods for personalized medicine discovery.
abstract: It is well documented that patients can show significant heterogeneous responses to treatments so the best treatment strategies may require adaptation over individuals and time. Recently, a number of new statistical methods have been developed to tackle the important problem of estimating personalized treatment rules using single-stage or multiple-stage clinical data. In this paper, we provide an overview of these methods and list a number of challenges.
authors: Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, 600 Highland Ave., Madison, WI 53792, USA.
authors: Yingqi
authors: Y
authors: Zhao
authors: Donglin
authors: D
authors: Zeng
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D055808:Drug Discovery / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D054539:Medication Therapy Management / Q000592:standards / Q000706:statistics & numerical data; D018579:Patient Selection; D057285:Precision Medicine / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D011897:Random Allocation
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