Publikationsdatum:
2024-04-11
Beschreibung:
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.
Schlagwort(e):
Vorhofflimmern
;
Fibrose
;
maschinelles Lernen
;
Bidomain
;
Modellierung des Herzens
;
atrial fibrillation
;
fibrosis
;
machine learning
;
bidomain
;
cardiac modeling
;
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TH Energy technology and engineering::THR Electrical engineering
Sprache:
Englisch
Format:
image/jpeg
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