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A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation
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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.
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Keywords
- Atrial Fibrillation
- Bidomain
- Cardiac modeling
- Electrical engineering
- Energy technology & engineering
- Fibrose
- Fibrosis
- Machine learning
- Maschinelles Lernen
- Modellierung des Herzens
- Technology, engineering, agriculture
- Vorhofflimmern
Links
DOI: 10.5445/KSP/1000143481Editions