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dc.contributor.authorCusimano, N. 
dc.contributor.authorGizzi, A.
dc.contributor.authorFenton, F.H.
dc.contributor.authorFilippi, S.
dc.contributor.authorGerardo-Giorda, L.
dc.date.accessioned2020-01-29T15:27:41Z
dc.date.available2020-01-29T15:27:41Z
dc.date.issued2020-05
dc.identifier.urihttp://hdl.handle.net/20.500.11824/1070
dc.description.abstractMicroscopic structural features of cardiac tissue play a fundamental role in determining complex spatio-temporal excitation dynamics at the macroscopic level. Recent efforts have been devoted to the development of mathematical models accounting for non-local spatio-temporal coupling able to capture these complex dynamics without the need of resolving tissue heterogeneities down to the micro-scale. In this work, we analyse in detail several important aspects affecting the overall predictive power of these modelling tools and provide some guidelines for an effective use of space-fractional models of cardiac electrophysiology in practical applications. Through an extensive computational study in simplified computational domains, we highlight the robustness of models belonging to different categories, i.e., physiological and phenomenological descriptions, against the introduction of non-locality, and lay down the foundations for future research and model validation against experimental data. A modern genetic algorithm framework is used to investigate proper parameterisations of the considered models, and the crucial role played by the boundary assumptions in the considered settings is discussed. Several numerical results are provided to support our claims.en_US
dc.description.sponsorshipItalian National Group of Mathematical Physics (GNFM-INdAM); NSF grant No. 1762553; NIH grant No. 1R01HL143450-01en_US
dc.formatapplication/pdfen_US
dc.language.isoengen_US
dc.rightsReconocimiento-NoComercial-CompartirIgual 3.0 Españaen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/en_US
dc.subjectCardiac dynamicsen_US
dc.subjectNon-local diffusionen_US
dc.subjectSpace-fractional modelen_US
dc.subjectComputational cardiologyen_US
dc.subjectParameter tuningen_US
dc.subjectGenetic algorithmen_US
dc.titleKey aspects for effective mathematical modelling of fractional-diffusion in cardiac electrophysiology: A quantitative studyen_US
dc.typeinfo:eu-repo/semantics/articleen_US
dc.identifier.doi10.1016/j.cnsns.2019.105152
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S100757041930471X#!en_US
dc.relation.projectIDES/1PE/SEV-2017-0718en_US
dc.relation.projectIDES/2PE/RTI2018-093416-B-I00en_US
dc.relation.projectIDEUS/BERC/BERC.2018-2021en_US
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen_US
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionen_US
dc.journal.titleCommunications in Nonlinear Science and Numerical Simulationen_US


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Reconocimiento-NoComercial-CompartirIgual 3.0 España
Except where otherwise noted, this item's license is described as Reconocimiento-NoComercial-CompartirIgual 3.0 España