##Statistics Seminar##\\ Department of Mathematical Sciences
^ **DATE:**|Thursday, October 8, 2020 |
^ **TIME:**|1:15pm -- 2:15pm |
^ **LOCATION:**|Zoom meeting |
^ **SPEAKER:**|Xinhai Zhang, Binghamton University |
^ **TITLE:**|Outcome Weighted Learning for Optimal Treatment Regimes |
\\
**Abstract**
There is increasing interest in discovering individualized treatment
rules for patients who have heterogeneous responses to treatment. In particular, one
aims to find an optimal individualized treatment rule which is a deterministic
function of patient specific characteristics maximizing expected clinical
outcome. Zhao et al. (2012) shown that estimating such an optimal treatment regime
is equivalent to a classification problem where each subject is weighted
proportional to his or her clinical outcome. Then they propose an outcome weighted
learning (OWL) approach based on the support vector machine framework. A few other
development after the original OWL will also be in this talk.