Identification and classification of arrhythmic heartbeats from electrocardiogram signals using feature induced optimal extreme gradient boosting algorithm-Reference-Cited by-同舟云学术

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Identification and classification of arrhythmic heartbeats from electrocardiogram signals using feature induced optimal extreme gradient boosting algorithm

Published:2023-10-09 Issue: Volume: Page:1-14
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Majumder S.¹,Bhattacharya S.¹,Debnath P.²,Ganguly B.³,Chanda M.¹

Affiliation:

1. Electronics and Communication Engineering Department, Meghnad Saha Institute of Technology, Kolkata, India

2. Department of Basic Sciences & Humanities, Techno International New Town, Kolkata, India

3. Department of Electrical Engineering, Meghnad Saha Institute of Technology, Kolkata, India

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2023.2265009

Reference51 articles.

1. SpEC: A system for patient specific ECG beat classification using deep residual network

2. Arrhythmia Classification with ECG signals based on the Optimization-Enabled Deep Convolutional Neural Network

3. Application of Cross Wavelet Transform for ECG Pattern Analysis and Classification

4. Agent-based beat-by-beat compression of 12-lead electrocardiogram signal using adaptive Fourier decomposition

5. TSFEL: Time Series Feature Extraction Library

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