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SUMMARY:Quantifying uncertainty in cardiovascular digital twins through mo
 del reduction\, Bayesian inference and propagation of model ensembles - Da
 niele Schiavazzi (University of Notre Dame)
DTSTART:20190607T110000Z
DTEND:20190607T113000Z
UID:TALK125722@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Cardiovascular disease is one of the leading cause of death in
  humans\, affecting the life of millions of people in the US and abroad. T
 his motivates research in numerical approaches for personalized hemodynami
 cs with the aim of improving early diagnosis\, treatment and medical devic
 e design. In this context\, cardiovascular models are experiencing an incr
 easing recent interest\, with the first FDA-approved technologies becoming
  a market reality\, creating new demand for such tools and pushing forward
  their clinical adoption. However\, deterministic analysis of cardiovascul
 ar flow is simply inadequate to provide an accurate characterization of th
 e patient physiology and new stochastic approaches need to be developed to
  efficiently quantify the effects of uncertainty from various sources\, e.
 g.\, errors and inconsistency in clinical measurements\, histological vari
 ability in vascular tissue and operator-dependent anatomical segmentation.
  In this talk\, recent efforts to quantify the confidence in predicted cli
 nical indicators from personalized hemodynamic models will be discussed\, 
 starting with the construction of zero-\, one- and three-dimensional repre
 sentations of the cardiovascular system. I will discuss the use of paralle
 l adaptive Markov chain Monte Carlo for estimating the parameters of reduc
 ed order compartmental models and how improved estimators can be construct
 ed using Bayesian updates at the compartment level. Approaches for uncerta
 inty propagation will also be discussed using estimators constructed from 
 a multi-resolution stochastic expansion of the quantities of interested as
  well as a multilevel/multifidelity Monte Carlo estimators. Applications w
 ill be presented in the context of coronary artery disease\, congenital he
 art disease and detection of pulmonary hypertension in patients affected b
 y heart failure with preserved ejection fraction (also known as diastolic 
 heart failure).
LOCATION:Seminar Room 1\, Newton Institute
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