In recent decades biomedical studies with living
probands (in vivo) and artificial experiments (in vitro) have been
complemented more and more by computation and simulation
(in silico). In silico techniques for medical engineering can give
for example enhanced information for the diagnosis and risk
stratification of cardiovascular disease, one of the most occurring
causes of death in the developed countries. Other use cases for in
silico methods are given by virtual prototyping and the
simulation of possible surgery outcomes. High reliability is a
requirement for cardiovascular diagnosis and risk stratification
methods especially with surgical decision-making. Given
uncertainties in the input data of a simulation, this implies a
necessity to quantify the uncertainties in simulation results.
Uncertainties can be propagated within a numerical simulation
by methods of Uncertainty Quantification (UQ)
