The contents of this deliverable are presented to demonstrate the proof-of-principle of the application of uncertainty quantification and sensitivity analysis to both aortic valve stenosis and heart failure patients. Sensitivity analysis will be used extensively in SIMCor for two specific objectives: 1) assessment/ranking of relevant model parameters for the output(s) of interest, and 2) design of the selection criteria for filtering during virtual cohort creation. This deliverable starts with the formal definition of uncertainty and sensitivity analysis that we adopted from literature. Thereafter, we will briefly explain the envisioned sensitivity analysis strategies and we will show preliminary results when applying these techniques to models with different levels of complexity and computational demands. These preliminary results demonstrate the feasibility of applying our sensitivity tools to relevant use cases. As uncertainty and sensitivity analysis are strongly related concepts, the uncertainty in model predictions follows almost directly from the sensitivity analyses applied.

SIMCor (In-Silico testing and validation of Cardiovascular IMplantable devices) has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101017578.