Detection of Life-Threatening Arrhythmias Using Feature Selection and Support Vector Machines-Reference-Cited by-同舟云学术

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Detection of Life-Threatening Arrhythmias Using Feature Selection and Support Vector Machines

Published:2014-03 Issue:3 Volume:61 Page:832-840
ISSN:0018-9294
Container-title:IEEE Transactions on Biomedical Engineering
language:
Short-container-title:IEEE Trans. Biomed. Eng.

Author:

Alonso-Atienza Felipe,Morgado Eduardo,Fernandez-Martinez Lorena,Garcia-Alberola Arcadi,Rojo-Alvarez Jose Luis

Funder

Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/10/6740863/06663664.pdf?arnumber=6663664

Cited by 168 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advanced integration of 2DCNN-GRU model for accurate identification of shockable life-threatening cardiac arrhythmias: a deep learning approach;Frontiers in Physiology;2024-07-12

2. SPTDMD-WST: Arrhythmia classification from spatiotemporal modes of dynamic mode decomposition using wavelet scattering transform;Biomedical Signal Processing and Control;2024-06

3. Prediction and Detection of Ventricular Fibrillation Using Complex Features and AI-Based Classification;Applied Sciences;2024-04-04

4. Hardware-Accelerated Neural Network Model for Early Prediction of Sudden Cardiac Arrest Based on Heart Rate Variability Metrics;2024-02-15

5. Detection of Shockable Arrhythmia From Electrocardiogram Signal Using Recurrence Quantification Analysis Based Deep Convolutional Neural Networks;IEEE Transactions on Instrumentation and Measurement;2024

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