Cargando…
POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium
The numerical simulation of multiple scenarios easily becomes computationally prohibitive for cardiac electrophysiology (EP) problems if relying on usual high-fidelity, full order models (FOMs). Likewise, the use of traditional reduced order models (ROMs) for parametrized PDEs to speed up the soluti...
Autores principales: | Fresca, Stefania, Manzoni, Andrea, Dedè, Luca, Quarteroni, Alfio |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8493298/ https://www.ncbi.nlm.nih.gov/pubmed/34630131 http://dx.doi.org/10.3389/fphys.2021.679076 |
Ejemplares similares
-
Deep learning-based reduced order models in cardiac electrophysiology
por: Fresca, Stefania, et al.
Publicado: (2020) -
Data integration for the numerical simulation of cardiac electrophysiology
por: Pagani, Stefano, et al.
Publicado: (2021) -
The Impact of Left Atrium Appendage Morphology on Stroke Risk Assessment in Atrial Fibrillation: A Computational Fluid Dynamics Study
por: Masci, Alessandro, et al.
Publicado: (2019) -
lifex-ep: a robust and efficient software for cardiac electrophysiology simulations
por: Africa, Pasquale Claudio, et al.
Publicado: (2023) -
Active Force Generation in Cardiac Muscle Cells: Mathematical Modeling and Numerical Simulation of the Actin-Myosin Interaction
por: Regazzoni, Francesco, et al.
Publicado: (2020)