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

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

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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 fib...

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Bibliographic Details
Main Author: Nagel, Claudia (auth)
Format: Electronic Book Chapter
Language:English
Published: KIT Scientific Publishing 2023
Series:Karlsruhe transactions on biomedical engineering 25
Subjects:
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 Access:OAPEN Library: download the publication
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Summary: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.
Physical Description:1 electronic resource (280 p.)
ISBN:KSP/1000155927
Access:Open Access

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