A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation : A Translational Study to Guide Ablation Therapy

• Autore: Patricio Sánchez Arciniegas Jorge
• Pubblicazione: Karlsruhe, : KIT Scientific Publishing, 2022
• Descrizione fisica: 1 electronic resource (162 p.)
• Soggetto topico: Electrical engineering
• Soggetto non controllato: Vorhofflimmern; Fibrose; maschinelles Lernen; Bidomain; Modellierung des Herzens; atrial fibrillation; fibrosis; machine learning; bidomain; cardiac modeling
• Sommario/riassunto: 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.
• Altri titoli varianti: Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation
• Titolo autorizzato: A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910576868403321
• Lo trovi qui: Univ. Federico II