activity
20152026
most citedModeling cardiac muscle fibers in ventricular and atrial electrophysiology simulations

128 citations · 990 across the 51 of their papers we have counts for

collaborators
Showing 2023 · math.NAShow all

8 papers · 2 filters

math.NA2023

Space--time Isogeometric Analysis of cardiac electrophysiology

P. F. Antonietti, L. Dedè, G. Loli +3

This work proposes a stabilized space--time method for the monodomain equation coupled with the Rogers--McCulloch ionic model, which is widely used to simulate electrophysiological…

math.NA2023

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Pasquale C. Africa, Roberto Piersanti, Francesco Regazzoni +6

Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-…

math.NA2023★ 3 cited

Real-time whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Matteo Salvador, Marina Strocchi, Francesco Regazzoni +3

Cardiac digital twins provide a physics and physiology informed framework to deliver predictive and personalized medicine. However, high-fidelity multi-scale cardiac models remain…

math.NA2023

Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: application to cardiac electromechanics

Michele Bucelli, Francesco Regazzoni, Luca Dede' +1

The accurate robust and efficient transfer of the deformation gradient tensor between meshes of different resolution is crucial in cardiac electromechanics simulations. We present…

math.NA2023★ 9 cited

A mathematical model to assess the effects of COVID-19 on the cardiocirculatory system

Andrea Tonini, Christian Vergara, Francesco Regazzoni +4

Impaired cardiac function has been described as a frequent complication of COVID-19-related pneumonia. To investigate possible underlying mechanisms, we represented the cardiovascu…

math.NA2023★ 14 cited

A Deep Learning algorithm to accelerate Algebraic Multigrid methods in Finite Element solvers of 3D elliptic PDEs

Matteo Caldana, Paola F. Antonietti, Luca Dede'

Algebraic multigrid (AMG) methods are among the most efficient solvers for linear systems of equations and they are widely used for the solution of problems stemming from the discr…

math.NA2023★ 27 cited

Discontinuous Galerkin Methods for Fisher-Kolmogorov Equation with Application to -Synuclein Spreading in Parkinson's Disease

Mattia Corti, Francesca Bonizzoni, Luca Dede' +2

This spreading of prion proteins is at the basis of brain neurodegeneration. This paper deals with the numerical modelling of the misfolding process of -synuclein in Parkinson's…

math.NA2023★ 49 cited

An electromechanics-driven fluid dynamics model for the simulation of the whole human heart

Alberto Zingaro, Michele Bucelli, Roberto Piersanti +3

We introduce a multiphysics and geometric multiscale computational model, suitable to describe the hemodynamics of the whole human heart, driven by a four-chamber electromechanical…