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Found 10 papers, 2 papers with code
Physics-informed Neural Network Estimation of Material Properties in Soft Tissue Nonlinear Biomechanical Models
The development of biophysical models for clinical applications is rapidly advancing in the research community, thanks to their predictive nature and their ability to assist the interpretation of clinical data.
Real-time whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations
The trained LNODEs provides a compact and efficient representation of the 3D-0D model in a latent space by means of a feedforward fully-connected Artificial Neural Network that retains 3 hidden layers with 13 neurons per layer and allows for 300x real-time numerical simulations of the cardiac function on a single processor of a standard laptop.
Latent Dynamics Networks (LDNets): learning the intrinsic dynamics of spatio-temporal processes
We propose a novel architecture, named Latent Dynamics Network (LDNet), which is able to discover low-dimensional intrinsic dynamics of possibly non-Markovian dynamical systems, thus predicting the time evolution of space-dependent fields in response to external inputs.
Modelling the COVID-19 epidemic and the vaccination campaign in Italy by the SUIHTER model
Several epidemiological models have been proposed to study the evolution of COVID-19 pandemic.
Modeling cardiac muscle fibers in ventricular and atrial electrophysiology simulations
Next we propose, for the first time, a LDRBM to be used for generating atrial fibers.
Numerical Analysis Computational Engineering, Finance, and Science Numerical Analysis
SUIHTER: A new mathematical model for COVID-19. Application to the analysis of the second epidemic outbreak in Italy
The COVID-19 epidemic is the last of a long list of pandemics that have affected humankind in the last century.
A cardiac electromechanics model coupled with a lumped parameters model for closed-loop blood circulation. Part II: numerical approximation
In the framework of accurate and efficient segregated schemes for 3D cardiac electromechanics and 0D cardiovascular models, we propose here a novel numerical approach to address the coupled 3D-0D problem introduced in Part I of this two-part series of papers.
Numerical Analysis Numerical Analysis
A Mathematical Dashboard for the Analysis of Italian COVID-19 Epidemic Data
An analysis of the COVID-19 epidemic is proposed on the basis of the epiMOX dashboard (publicly accessible at https://www. epimox. polimi. it) that deals with data of the epidemic trends and outbreaks in Italy from late February 2020.
Deep learning-based reduced order models in cardiac electrophysiology
These systems describe the cardiac action potential, that is the polarization/depolarization cycle occurring at every heart beat that models the time evolution of the electrical potential across the cell membrane, as well as a set of ionic variables.
Biophysically detailed mathematical models of multiscale cardiac active mechanics
We propose four novel mathematical models, describing the microscopic mechanisms of force generation in the cardiac muscle tissue, which are suitable for multiscale numerical simulations of cardiac electromechanics.
