Original paper
Detection of Atrial Fibrillation Using a Machine Learning Approach
Abstract
The atrial fibrillation (AF) is one of the most well-known cardiac arrhythmias in clinical practice, with a prevalence of 1–2% in the community, which can increase the risk of stroke and myocardial infarction. The detection of AF electrocardiogram (ECG) can improve the early detection of diagnosis. In this paper, we have further developed a framework for processing the ECG signal in order to determine the AF episodes. We have implemented machine...
Paper Details
Title
Detection of Atrial Fibrillation Using a Machine Learning Approach
Published Date
Nov 26, 2020
Journal
Volume
11
Issue
12
Pages
549 - 549
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Notes
History