LEADER 02138nam  2200445z- 450 
001 9910576868403321
005 20231214133036.0
035   $a(CKB)5860000000051234
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/84372
035   $a(EXLCZ)995860000000051234
100   $a20202206d2022      |y             0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aA Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation$eA Translational Study to Guide Ablation Therapy
210   $aKarlsruhe$cKIT Scientific Publishing$d2022
215   $a1 electronic resource (162 p.)
225 1 $aKarlsruhe transactions on biomedical engineering
311   $a3-7315-1170-3 
330   $aThe 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.
517   $aMultiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation
606   $aElectrical engineering$2bicssc
610   $aVorhofflimmern
610   $aFibrose
610   $amaschinelles Lernen
610   $aBidomain
610   $aModellierung des Herzens
610   $aatrial fibrillation
610   $afibrosis
610   $amachine learning
610   $abidomain
610   $acardiac modeling
615  7$aElectrical engineering
700   $aPatricio Sánchez Arciniegas$b Jorge$4auth$01329332
906   $aBOOK
912   $a9910576868403321
996   $aA Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation$93039439
997   $aUNINA