A Novel Feature Extraction Technique for ECG Arrhythmia Classification Using ML-Reference-Cited by-同舟云学术

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A Novel Feature Extraction Technique for ECG Arrhythmia Classification Using ML

Published:2023-11-14 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
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Author:

Rahman Mohammad Mominur¹,Islam Ashhadul¹,Charni Skander²,Bensmail Halima³,Hilbel Thomas⁴,Belhaouari Samir Brahim¹

Affiliation:

1. College of Science and Engineering, Hamad Bin Khalifa University,Division of Information and Computing Technology,Doha,Qatar

2. College of Engineering, Qatar University,Doha,Qatar

3. Qatar Computing Research Institute (QCRI),Computational Biology group (CS&E),Doha,Qatar

4. Westphalian University of Applied Sciences,Department of Electrical Engineering and Applied Sciences,Gelsenkirchen,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10361260/10360496/10360505.pdf?arnumber=10360505

Reference36 articles.

1. Label-Dependent Feature Extraction in Social Networks for Node Classification

2. A scalable multi-level feature extraction technique to detect malicious executables

3. Feature Extraction for Classification in the Data Mining Process;Pechenizkiy;International Journal “Information Theories & Applications,2008

4. A Novel Approach for Feature Extraction and Selection on MRI Images for Brain Tumor Classification

5. A Hybrid Method of Feature Extraction for Tumor Classification Using Microarray Gene Expression Data

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