Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction-Reference-Cited by-同舟云学术

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Hybrid Feature Selection and Classifying Stages through Electrocardiogram (ECG) Signal for Heart Disease Prediction

Published:2023-12-27 Issue: Volume: Page:
ISSN:
Container-title:RAiSE-2023
language:
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Author:

Kumar Babu¹,Soundararajan Radhakrishnan²,Natesan Kanimozhi¹,Santhi Roobini Maridhas³

Affiliation:

1. Department of Computational Intelligence, SRM Institute of Science & Technology, Kattankulathur 603203, India

2. Department of Mathematics, SRM TRP Engineering College, Trichy 621105, India

3. Department of Computer Science & Engineering, Sathyabama Institute of Science & Technology, Chennai 600119, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/126/pdf

Reference22 articles.

1. Kamaruddin, N.H., Murugappan, M., and Omar, M.I. (2012, January 5–6). Early prediction of Cardiovascular Diseases using ECG signal. Proceedings of the IEEE Student Conference on Research and Development, Pulau Pinang, Malaysia.

2. Tabassum, T., and Islam, M. (2016, January 22–24). An approach of cardiac disease prediction by analyzing ECG signal. Proceedings of the 3rd International Conference on Electrical Engineering and Information Communication Technology, Dhaka, Bangladesh.

3. Zhang, W., Yu, L., Ye, L., Zhuang, W., and Ma, F. (2018, January 22–24). ECG signal classification with deep learning for heart disease identification. Proceedings of the International Conference on Big Data and Artificial Intelligence, Beijing, China.

4. Murukesan, L., Murugappan, M., and Iqbal, M. (2013, January 8–10). Sudden cardiac death prediction using ECG signal derivative (heart rate variability): A review. Proceedings of the IEEE 9th international colloquium on signal processing and its applications, Kuala Lumpur, Malaysia.

5. Sakhare, P.B., and Ghongade, R. (2015, January 17–20). An approach for ECG beats classification using adaptive neuro fuzzy inference system. Proceedings of the Annual IEEE India Conference, New Delhi, India.

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