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Activity Number: 46
Type: Invited
Date/Time: Sunday, August 9, 2015 : 4:00 PM to 5:50 PM
Sponsor: ASA
Abstract #317700 View Presentation
Title: Estimating Dynamic Treatment Regimens Using SMARTs and Reinforcement Learning
Author(s): Michael Kosorok*
Companies: The University of North Carolina at Chapel Hill
Keywords:
Abstract:

We describe several statistical approaches for tailoring treatment in the multi-stage setting. These dynamic treatment regimens (DTRs) use patient baseline variables and accumulated patient history to tailor treatments to the individual as well as to adapt over time. Sequential Multiple Assignment Randomized Trials (SMARTs) are efficient designs for collecting data from patients to enable estimation of DTRs. Reinforcement learning methods, which have their origins in computer science, are statistical approaches for estimating DTRs from SMARTs and other appropriate designs. We will also describe the basics of Q-learning, a popular method for reinforcement learning.


Authors who are presenting talks have a * after their name.

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