Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillatorResearch in context

Dynamic prediction of malignant ventricular arrhythmias using neural networks in patients with an implantable cardioverter-defibrillatorResearch in context

Summary: Background: Risk stratification for ventricular arrhythmias currently relies on static measurements that fail to adequately capture dynamic interactions between arrhythmic substrate and triggers over time. We trained and internally validated a dynamic machine learning (ML) model and neural...

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Bibliographic Details
Main Authors: Maarten Z.H. Kolk, Samuel Ruipérez-Campillo, Laura Alvarez-Florez, Brototo Deb, Erik J. Bekkers, Cornelis P. Allaart, Anne-Lotte C.J. Van Der Lingen, Paul Clopton, Ivana Išgum, Arthur A.M. Wilde, Reinoud E. Knops, Sanjiv M. Narayan, Fleur V.Y. Tjong
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:EBioMedicine
Subjects:
Cardiology
Machine learning
Deep learning
Electrocardiography
Sudden cardiac death
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396423005030

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http://www.sciencedirect.com/science/article/pii/S2352396423005030

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