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SUMMARY:Jana de Wiljes (Universität Potsdam\, DE)
DTSTART:20200629T120000Z
DTEND:20200629T124500Z
DTSTAMP:20260423T022740Z
UID:OWMADS/11
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/OWMADS/11/">
 Sequential learning for decision support under uncertainty</a>\nby Jana de
  Wiljes (Universität Potsdam\, DE) as part of One World seminar: Mathemat
 ical Methods for Arbitrary Data Sources (MADS)\n\n\nAbstract\nIn many appl
 icational areas there is a need to determine a control variable that optim
 izes a pre-specified objective. This problem is particularly challenging w
 hen knowledge on the underlying dynamics is subject to various sources of 
 uncertainty.  A scenario such as that  arises for instance in the context 
 of therapy individualization to improve the efficacy and safety of medical
  treatment. Mathematical models describing the pharmacokinetics and pharma
 codynamics of a drug together with data on associated biomarkers can be le
 veraged to support decision-making by predicting therapy outcomes. We pres
 ent a continuous learning strategy which follows a novel sequential Monte 
 Carlo tree search approach and explore how the underlying uncertainties re
 flect in the approximated control variable.\n
LOCATION:https://researchseminars.org/talk/OWMADS/11/
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