Mathematical and numerical modelling of the cardiovascular system is a research topic that
has attracted remarkable interest from the mathematical community because of its intrinsic …

Aortic dissection continues to be responsible for significant morbidity and mortality, although
recent advances in medical data assimilation and in experimental and in silico models have …

This article provides an overview of multi-fidelity modeling trends. Fidelity in modeling refers
to the level of detail and accuracy provided by a predictive model or simulation. Generally …

Multifidelity surrogates are essential in cases where it is not affordable to have more than a
few high-fidelity samples, but it is affordable to have as many low-fidelity samples as …

Mathematical and numerical modelling of the human cardiovascular system has attracted
remarkable research interest due to its intrinsic mathematical difficulty and the increasing …

As we shift from population‐based medicine towards a more precise patient‐specific regime
guided by predictions of verified and well‐established cardiovascular models, an urgent …

Optimization and uncertainty quantification have been playing an increasingly important role
in computational hemodynamics. However, existing methods based on principled modeling …

Quantifying biomechanical properties of the human vasculature could deepen our
understanding of cardiovascular diseases. Standard nonlinear regression in constitutive …

We present a simple open-source semi-intrusive computational method to propagate
uncertainties through hyperelastic models of soft tissues. The proposed method is up to two …

We present a probabilistic deep learning methodology that enables the construction of
predictive data-driven surrogates for stochastic systems. Leveraging recent advances in …