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dc.contributor.authorPatricio Sánchez Arciniegas, Jorge
dc.date.accessioned2022-06-21T04:02:48Z
dc.date.available2022-06-21T04:02:48Z
dc.date.issued2022
dc.date.submitted2022-06-20T19:09:54Z
dc.identifierONIX_20220620_9783731511700_75
dc.identifier1864-5933
dc.identifierhttps://library.oapen.org/handle/20.500.12657/56965
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/84372
dc.description.abstractThe atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.
dc.languageEnglish
dc.relation.ispartofseriesKarlsruhe transactions on biomedical engineering
dc.rightsopen access
dc.subject.otherVorhofflimmern
dc.subject.otherFibrose
dc.subject.othermaschinelles Lernen
dc.subject.otherBidomain
dc.subject.otherModellierung des Herzens
dc.subject.otheratrial fibrillation
dc.subject.otherfibrosis
dc.subject.othermachine learning
dc.subject.otherbidomain
dc.subject.othercardiac modeling
dc.titleA Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation
dc.title.alternativeA Translational Study to Guide Ablation Therapy
dc.typebook
oapen.identifier.doi10.5445/KSP/1000143481
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2
oapen.relation.isbn9783731511700
oapen.imprintKIT Scientific Publishing
oapen.pages162
oapen.place.publicationKarlsruhe
dc.seriesnumber24


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