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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Electrocardiogram Analysis by Means of Empirical Mode Decomposition-Based Methods and Convolutional Neural Networks for Sudden Cardiac Death Detection
Manuel A. Centeno-Bautista, Angel H. Rangel-Rodriguez, Andrea V. Perez-Sanchez, et al.
Applied Sciences (2023) Vol. 13, Iss. 6, pp. 3569-3569
Open Access | Times Cited: 11

Showing 11 citing articles:

Sudden cardiac death prediction based on the complete ensemble empirical mode decomposition method and a machine learning strategy by using ECG signals
Manuel A. Centeno-Bautista, Andrea V. Perez-Sanchez, Juan P. Amézquita-Sánchez, et al.
Measurement (2024) Vol. 236, pp. 115052-115052
Closed Access | Times Cited: 6
A novel method for early prediction of sudden cardiac death through nonlinear feature extraction from ECG signals
Fatemeh Danesh Jablo, Hamed Danandeh Hesar
Physical and Engineering Sciences in Medicine (2025)
Closed Access
Detection of Ventricular Fibrillation Using Ensemble Empirical Mode Decomposition of ECG Signals
Seungrok Oh, Young-Seok Choi
Electronics (2024) Vol. 13, Iss. 4, pp. 695-695
Open Access | Times Cited: 2
The Use of Empirical Mode Decomposition on Heart Rate Variability Signals to Assess Autonomic Neuropathy Progression in Type 2 Diabetes
Sandra Cossul, Felipe Rettore Andreis, M. A. Favretto, et al.
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7824-7824
Open Access | Times Cited: 5
A pioneering approach for early prediction of sudden cardiac death via morphological ECG features measurement and ensemble growing techniques
Shaik Karimulla, Dipti Patra
Computers & Electrical Engineering (2024) Vol. 120, pp. 109740-109740
Closed Access | Times Cited: 1
Early prediction of sudden cardiac death using multimodal fusion of ECG Features extracted from Hilbert-Huang and wavelet transforms with explainable vision transformer and CNN models
Hardik Telangore, Victor Azad, Manish Sharma, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 257, pp. 108455-108455
Closed Access | Times Cited: 1
Combining mathematical model for HRV mapping and machine learning to predict sudden cardiac death
Shahrzad Marjani, Mohammad Karimi Moridani
Computer Methods and Programs in Biomedicine Update (2023) Vol. 4, pp. 100112-100112
Open Access | Times Cited: 2
Heart Murmur Classification Using a Capsule Neural Network
Yu‐Ting Tsai, Yu-Hsuan Liu, Ziwei Zheng, et al.
Bioengineering (2023) Vol. 10, Iss. 11, pp. 1237-1237
Open Access | Times Cited: 2
An Optimal Methodology for Early Prediction of Sudden Cardiac Death Using Advanced Heart Rate Variability Features of ECG Signal
Shaik Karimulla, Dipti Patra
Arabian Journal for Science and Engineering (2023) Vol. 49, Iss. 5, pp. 6725-6741
Closed Access | Times Cited: 2
Clinical sudden cardiac death risk prediction: A grid search support vector machine multimodel base on ventricular fibrillation visualization features
Chao-Xin Xie, Liang-Hung Wang, Yanting Yu, et al.
Computers & Electrical Engineering (2024) Vol. 123, pp. 110022-110022
Closed Access
Prediction of Cardiac Arrest by the Hybrid Approach of Soft Computing and Machine Learning
Subrata Kumar Nayak, Sateesh Kumar Pradhan, Sujogya Mishra, et al.
International Journal of Advanced Computer Science and Applications (2023) Vol. 14, Iss. 7
Open Access | Times Cited: 1
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