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

• 1. Verfasser: Nagel, Claudia (auth)
• Format: Elektronisch Buchkapitel
• Sprache: Englisch
• Veröffentlicht: KIT Scientific Publishing 2023
• Schriftenreihe: Karlsruhe transactions on biomedical engineering
• Schlagworte: 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
• Online-Zugang: DOAB: download the publication; DOAB: description of the publication

Zusammenfassung

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.

Beschreibung

1 electronic resource (280 p.)

ISBN

KSP/1000155927

Zugangseinschränkungen

Open Access