BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Talks.cam//talks.cam.ac.uk// X-WR-CALNAME:Talks.cam BEGIN:VEVENT SUMMARY:The role of uncertainty and sensitivity analysis in patient-tailor ed cardiovascular models - Wouter Huberts (University of Maastricht\; Tech nische Universiteit Eindhoven) DTSTART:20190605T110000Z DTEND:20190605T113000Z UID:TALK125557@talks.cam.ac.uk CONTACT:INI IT DESCRIPTION:Physics-based patient-specific models have the potential to su pport physicians in decision-making during diagnosis and intervention plan ning.To adapt these models to personalized conditions\, patient-specific i nput parameters should be available. In clinics\, the number of measurable input parameters is limited which results in sparse datasets. In addition \, patient data are compromised with uncertainty. These uncertain and inco mplete input datasets will result in model output uncertainties. By means of a global variance-based sensitivity analysis it can be assessed which u ncertain input parameters are most rewarding to measure more accurately fo r reducing output uncertainty (parameter prioritization) and which irrele vant model parameters can be fixed within their uncertainty domain (parame ter fixing). Such an analysis can therefore give directions for input meas urement improvement.
In this work\, we will discuss the role of uncert ainty and sensitivity analysis in patient-tailored modeling. In addition\, we will present a two-step variance-based sensitivity analysis method for a cardiovascular model with many model parameters. In the first step\, we perform a screening method to reduce the parameter input space\, followed by generalized polynomial chaos expansion. Furthermore\, we will introduc e an adaptive generalized polynomial chaos expansion method which is an ef ficient variance-based sensitivity analysis approach for computationally e xpensive models and was first introduced by Blatman et al. in the field of structural reliability engineering. LOCATION:Seminar Room 1\, Newton Institute END:VEVENT END:VCALENDAR