Campuses:

Policy learning

Friday, September 15, 2017 - 9:00am - 10:00am
Michael Kosorok (University of North Carolina, Chapel Hill)
Estimating individualized treatment rules is a central task of personalized or precision medicine. In this presentation, we review several new developments in outcome weighted learning for identifying individualized treatment rules for two challenging settings: dose finding and treatment selection under right censoring. In the former, we develop an approach which involves the use of two different kernels; and in the later, we use random forests to address censoring before applying outcome weighted learning.
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