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

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
Format: eBook
Language:English
Published: KIT Scientific Publishing 2023
Series:Karlsruhe transactions on biomedical engineering
Subjects:
Electrophysiologische Modellierung Und Simulation; Elektrokardiogramm; Maschinelles Lernen; Vorhofflimmern; Statistisches Shape Modell; Electrophysiological Modeling And Simulation; Electrocardiogram; Machine Learning; Atrial Fibrillation; Statistical Shape Model
Electrical Engineering
Online Access:
Collection: OAPEN - Collection details see MPG.ReNa
Description
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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by-sa/4.0/
Physical Description:280 p.
ISBN:KSP/1000155927

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