A Deep Belief Network Model for Automatic Atrial Fibrillation Detection
Author:
Affiliation:
1. School of Electronics Engineering, Vellore Institute of Technology, Chennai, India
2. Centre for Smart Grid Technologies, School of Electronics Engineering, Vellore Institute of Technology, Chennai, India
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science
Link
https://www.tandfonline.com/doi/pdf/10.1080/03772063.2023.2167739
Reference45 articles.
1. Automated detection of atrial fibrillation using long short-term memory network with RR interval signals
2. Automatic Atrial Fibrillation Detection Based on Heart Rate Variability and Spectral Features
3. B. Yu, B. Zhang, L. Xu, P. Fang, and J. Hu. Automatic Detection of Atrial Fibrillation from Ballistocardiogram (BCG) Using Wavelet Features and Machine Learning. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019, July, pp. 4322–5. IEEE.
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