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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:

A Novel Wavelet Transform-Homogeneity Model for Sudden Cardiac Death Prediction Using ECG Signals
Juan P. Amézquita-Sánchez, Martin Valtierra‐Rodriguez, Hojjat Adeli, et al.
Journal of Medical Systems (2018) Vol. 42, Iss. 10
Closed Access | Times Cited: 58

Showing 1-25 of 58 citing articles:

A novel methodology for automated differential diagnosis of mild cognitive impairment and the Alzheimer’s disease using EEG signals
Juan P. Amézquita-Sánchez, Nadia Mammone, Francesco Carlo Morabito, et al.
Journal of Neuroscience Methods (2019) Vol. 322, pp. 88-95
Closed Access | Times Cited: 97
An Automated Strategy for Early Risk Identification of Sudden Cardiac Death by Using Machine Learning Approach on Measurable Arrhythmic Risk Markers
Dakun Lai, Yifei Zhang, Xinshu Zhang, et al.
IEEE Access (2019) Vol. 7, pp. 94701-94716
Open Access | Times Cited: 91
Unilateral sensorineural hearing loss identification based on double-density dual-tree complex wavelet transform and multinomial logistic regression
Shuihua Wang‎, Yudong Zhang, Ming Yang, et al.
Integrated Computer-Aided Engineering (2019) Vol. 26, Iss. 4, pp. 411-426
Open Access | Times Cited: 76
A Time Series Forecasting Approach Based on Nonlinear Spiking Neural Systems
Lifan Long, Qian Liu, Hong Peng, et al.
International Journal of Neural Systems (2022) Vol. 32, Iss. 08
Closed Access | Times Cited: 48
Machine learning of electrophysiological signals for the prediction of ventricular arrhythmias: systematic review and examination of heterogeneity between studies
Maarten Z H Kolk, Brototo Deb, Samuel Ruipérez-Campillo, et al.
EBioMedicine (2023) Vol. 89, pp. 104462-104462
Open Access | Times Cited: 32
Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection
Amjed Al Fahoum, Ala’a Zyout
International Journal of Neural Systems (2024) Vol. 34, Iss. 09
Closed Access | Times Cited: 10
A new epileptic seizure prediction model based on maximal overlap discrete wavelet packet transform, homogeneity index, and machine learning using ECG signals
Andrea V. Perez-Sanchez, Juan P. Amézquita-Sánchez, Martin Valtierra‐Rodriguez, et al.
Biomedical Signal Processing and Control (2023) Vol. 88, pp. 105659-105659
Closed Access | Times Cited: 21
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: 7
Multi-Label ECG Signal Classification Based on Ensemble Classifier
Zhanquan Sun, Chaoli Wang, Yangyang Zhao, et al.
IEEE Access (2020) Vol. 8, pp. 117986-117996
Open Access | Times Cited: 45
Emergence of Artificial Intelligence and Machine Learning Models in Sudden Cardiac Arrest: A Comprehensive Review of Predictive Performance and Clinical Decision Support
Hritvik Jain, Mohammed Dheyaa Marsool Marsool, Ramez M. Odat, et al.
Cardiology in Review (2024)
Closed Access | Times Cited: 5
Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review
Asma Alamgir, Osama Mousa, Zubair Shah
JMIR Medical Informatics (2021) Vol. 9, Iss. 12, pp. e30798-e30798
Open Access | Times Cited: 28
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
A brain-inspired model for multi-step forecasting of malignant arrhythmias
Yun Kwan Kim, Insung Choi, Sun Jung Lee, et al.
Expert Systems with Applications (2025), pp. 126373-126373
Closed Access
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
A New Methodology Based on EMD and Nonlinear Measurements for Sudden Cardiac Death Detection
Olivia Vargas-Lopez, Juan P. Amézquita-Sánchez, J. Jesus De-Santiago-Perez, et al.
Sensors (2019) Vol. 20, Iss. 1, pp. 9-9
Open Access | Times Cited: 32
Sudden Cardiac Arrest (SCA) Prediction Using ECG Morphological Features
M. Murugappan, Lakshmi Murugesan, S. Jerritta, et al.
Arabian Journal for Science and Engineering (2020) Vol. 46, Iss. 2, pp. 947-961
Closed Access | Times Cited: 29
Accurate Prediction of Sudden Cardiac Death Based on Heart Rate Variability Analysis Using Convolutional Neural Network
Febriyanti Panjaitan, Siti Nurmaini, Radiyati Umi Partan
Medicina (2023) Vol. 59, Iss. 8, pp. 1394-1394
Open Access | Times Cited: 10
IoT-based emergency cardiac death risk rescue alert system
Shafiq Ul Rehman, Ibrahim Sadek, Binhua Huang, et al.
MethodsX (2024) Vol. 13, pp. 102834-102834
Open Access | Times Cited: 3
Prediction of cardiovascular disease from ECG using multi-scale and hybrid 1D–2D convolution-based residual attention network with adaptive STFT
L. Dharani, G. Victo Sudha George, S. Geetha
Australian Journal of Electrical & Electronics Engineering (2025), pp. 1-19
Closed Access
Predicting Ventricular Fibrillation Through Deep Learning
Li-Ming Tseng, Vincent S. Tseng
IEEE Access (2020) Vol. 8, pp. 221886-221896
Open Access | Times Cited: 25
A new damage indicator based on homogeneity and wireless accelerometers for evaluating the structural condition of a cable-stayed bridge
Martin Valtierra‐Rodriguez, José M. Machorro-López, Juan P. Amézquita-Sánchez, et al.
Developments in the Built Environment (2023) Vol. 14, pp. 100166-100166
Open Access | Times Cited: 7
A novel approach for early prediction of sudden cardiac death (SCD) using hybrid deep learning
Rabin Kaspal, Abeer Alsadoon, P. W. C. Prasad, et al.
Multimedia Tools and Applications (2020) Vol. 80, Iss. 5, pp. 8063-8090
Closed Access | Times Cited: 19
EPILEPTIC SEIZURE PREDICTION USING WAVELET TRANSFORM, FRACTAL DIMENSION, SUPPORT VECTOR MACHINE, AND EEG SIGNALS
Andrea V. Perez-Sanchez, Martin Valtierra‐Rodriguez, Carlos A. Perez-Ramirez, et al.
Fractals (2022) Vol. 30, Iss. 07
Closed Access | Times Cited: 11
Intelligent prediction of sudden cardiac death based on multi-domain feature fusion of heart rate variability signals
Jianli Yang, Zhiqiang Sun, Weiwei Zhu, et al.
EURASIP Journal on Advances in Signal Processing (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 6
Wavelet Transform-Statistical Time Features-Based Methodology for Epileptic Seizure Prediction Using Electrocardiogram Signals
Andrea V. Perez-Sanchez, Carlos A. Perez-Ramirez, Martin Valtierra‐Rodriguez, et al.
Mathematics (2020) Vol. 8, Iss. 12, pp. 2125-2125
Open Access | Times Cited: 15
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