January 19, 2022, 3:00-4:00 pm (Swedish time)
Title: We used Reinforcement Learning; but did it work?
Abstract: Reinforcement Learning provides an attractive suite of online learning methods for personalizing interventions in a Digital Health. However after an reinforcement learning algorithm has been run in a clinical study, how do we assess whether personalization occurred? We might find users for whom it appears that the algorithm has indeed learned in which contexts the user is more responsive to a particular intervention. But could this have happened completely by chance? We discuss some first approaches to addressing these questions..
Susan A. Murphy is a Radcliffe Alumnae Professor at Harvard Radcliffe Institute and a professor of statistics and computer science at the Harvard John A. Paulson School of Engineering and Applied Sciences. She leads the Statistical Reinforcement Learning Lab, working on the development of data analytic algorithms and methods for informing sequential decision making in health. In particular for (1) constructing individualized sequences of treatments (a.k.a., adaptive interventions) for use in informing clinical decision making and (2) constructing real time individualized sequences of treatments (a.k.a., Just-in-Time Adaptive Interventions) delivered by mobile devices. For her work on trial designs and analytics, Dr. Murphy was awarded a McArthur Fellowship in 2013, in 2014 she was elected a member of the National Academy of Medicine and in 2016 she was elected a member of the National Academy of Sciences of the US National Academies.
19 January, 2022, 15:00
19 January, 2022, 16:00