Multiscale Cohort Modeling of Atrial Electrophysiology Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms

• Autore principale: Nagel, Claudia (auth)
• Natura: Elettronico Capitolo di libro
• Lingua: inglese
• Pubblicazione: KIT Scientific Publishing 2023
• Serie: Karlsruhe transactions on biomedical engineering 25
• Soggetti: Electrical engineering; Electrophysiologische Modellierung und Simulation; Elektrokardiogramm; Maschinelles Lernen; Vorhofflimmern; Statistisches Shape Modell; electrophysiological modeling and simulation; electrocardiogram; machine learning; atrial fibrillation; statistical shape model
• Accesso online: OAPEN Library: download the publication; OAPEN Library: description of the publication

Riassunto

An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.

Descrizione fisica

1 electronic resource (280 p.)

ISBN

KSP/1000155927

Accesso

Open Access