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

We present a new, computationally efficient framework to perform forward uncertainty quantification (UQ) in cardiac electrophysiology. We consider the monodomain model to describe the electrical activity in the cardiac tissue, coupled with the Aliev‐Panfilov model to characterize the ionic activity...

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Detalles Bibliográficos
Autores principales: Pagani, Stefano, Manzoni, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244126/
https://www.ncbi.nlm.nih.gov/pubmed/33599106
http://dx.doi.org/10.1002/cnm.3450