02155nam 2200457z- 450 991057686840332120220621(CKB)5860000000051234(oapen)https://directory.doabooks.org/handle/20.500.12854/84372(oapen)doab84372(EXLCZ)99586000000005123420202206d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierA Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial FibrillationA Translational Study to Guide Ablation TherapyKarlsruheKIT Scientific Publishing20221 online resource (162 p.)Karlsruhe transactions on biomedical engineering3-7315-1170-3 The 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.Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial FibrillationElectrical engineeringbicsscatrial fibrillationbidomainBidomaincardiac modelingFibrosefibrosismachine learningmaschinelles LernenModellierung des HerzensVorhofflimmernElectrical engineeringPatricio Sánchez Arciniegas Jorgeauth1329332BOOK9910576868403321A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation3039439UNINA