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.
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Nagel, C. 2023. Multiscale Cohort Modeling of Atrial Electrophysiology : Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000155927
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Veröffentlicht am 24. April 2023
Englisch
280
Paperback | 978-3-7315-1281-3 |