Creation and application of virtual patient cohorts of heart models

SA Niederer, Y Aboelkassem… - … of the Royal …, 2020 - royalsocietypublishing.org
Patient-specific cardiac models are now being used to guide therapies. The increased use
of patient-specific cardiac simulations in clinical care will give rise to the development of …

Characterization of the COVID-19 pandemic and the impact of uncertainties, mitigation strategies, and underreporting of cases in South Korea, Italy, and Brazil

RF Reis, B de Melo Quintela… - Chaos, Solitons & …, 2020 - Elsevier
Abstract By April 7th, 2020, the Coronavirus disease 2019 (COVID-19) has infected one and
a half million people worldwide, accounting for over 80 thousand of deaths in 209 countries …

Polygonal surface processing and mesh generation tools for the numerical simulation of the cardiac function

M Fedele, A Quarteroni - International Journal for Numerical …, 2021 - Wiley Online Library
In order to simulate the cardiac function for a patient‐specific geometry, the generation of the
computational mesh is crucially important. In practice, the input is typically a set of …

Using machine learning to characterize heart failure across the scales

M Peirlinck, F Sahli Costabal, KL Sack, JS Choy… - … and modeling in …, 2019 - Springer
Heart failure is a progressive chronic condition in which the heart undergoes detrimental
changes in structure and function across multiple scales in time and space. Multiscale …

Uncertainty quantification and sensitivity analysis of left ventricular function during the full cardiac cycle

JO Campos, J Sundnes… - … Transactions of the …, 2020 - royalsocietypublishing.org
Patient-specific computer simulations can be a powerful tool in clinical applications, helping
in diagnostics and the development of new treatments. However, its practical use depends …

Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning

S Pagani, A Manzoni - International Journal for Numerical …, 2021 - Wiley Online Library
We present a new, computationally efficient framework to perform forward uncertainty
quantification (UQ) in cardiac electrophysiology. We consider the monodomain model to …

Bayesian optimisation for efficient parameter inference in a cardiac mechanics model of the left ventricle

A Borowska, H Gao, A Lazarus… - International Journal for …, 2022 - Wiley Online Library
We consider parameter inference in cardio‐mechanic models of the left ventricle, in
particular the one based on the Holtzapfel‐Ogden (HO) constitutive law, using clinical in vivo …

A poroelastic approach for modelling myocardial oedema in acute myocarditis

WJ Lourenço, RF Reis, R Ruiz-Baier… - Frontiers in …, 2022 - frontiersin.org
Myocarditis is a general set of mechanisms that manifest themselves into the inflammation of
the heart muscle. In 2017, more than 3 million people were affected by this disease …

Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics

A Lazarus, D Dalton, D Husmeier, H Gao - Biomechanics and Modeling in …, 2022 - Springer
Personalized computational cardiac models are considered to be a unique and powerful
tool in modern cardiology, integrating the knowledge of physiology, pathology and …

Unsupervised stochastic learning and reduced order modeling for global sensitivity analysis in cardiac electrophysiology models

N El Moçayd, Y Belhamadia, M Seaid - Computer Methods and Programs …, 2024 - Elsevier
Abstract Background and Objective: Numerical simulations in electrocardiology are often
affected by various uncertainties inherited from the lack of precise knowledge regarding …