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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:

Computer-aided diagnosis of atrial fibrillation based on ECG Signals: A review
Yuki Hagiwara, Hamido Fujita, Shu Lih Oh, et al.
Information Sciences (2018) Vol. 467, pp. 99-114
Closed Access | Times Cited: 171

Showing 1-25 of 171 citing articles:

Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals
Türker Tuncer, Şengül Doğan, Paweł Pławiak, et al.
Knowledge-Based Systems (2019) Vol. 186, pp. 104923-104923
Closed Access | Times Cited: 193
Artificial Intelligence in Cardiology: Present and Future
Francisco López-Jiménez, Zachi I. Attia, Adelaide M. Arruda‐Olson, et al.
Mayo Clinic Proceedings (2020) Vol. 95, Iss. 5, pp. 1015-1039
Open Access | Times Cited: 192
BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series
Bin Zhou, Shenghua Liu, Bryan Hooi, et al.
(2019), pp. 4433-4439
Open Access | Times Cited: 174
Detecting and interpreting myocardial infarction using fully convolutional neural networks
Nils Strodthoff, Claas Strodthoff
Physiological Measurement (2018) Vol. 40, Iss. 1, pp. 015001-015001
Open Access | Times Cited: 172
Point-of-care screening for heart failure with reduced ejection fraction using artificial intelligence during ECG-enabled stethoscope examination in London, UK: a prospective, observational, multicentre study
Patrik Bächtiger, Camille F Petri, Francesca E Scott, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 2, pp. e117-e125
Open Access | Times Cited: 96
Computer Aided detection for fibrillations and flutters using deep convolutional neural network
Hamido Fujita, Dalibor Cimr
Information Sciences (2019) Vol. 486, pp. 231-239
Closed Access | Times Cited: 134
DENS-ECG: A deep learning approach for ECG signal delineation
Abdolrahman Peimankar, Sadasivan Puthusserypady
Expert Systems with Applications (2020) Vol. 165, pp. 113911-113911
Open Access | Times Cited: 126
A deep learning approach for atrial fibrillation signals classification based on convolutional and modified Elman neural network
Jibin Wang
Future Generation Computer Systems (2019) Vol. 102, pp. 670-679
Closed Access | Times Cited: 105
Multi-domain modeling of atrial fibrillation detection with twin attentional convolutional long short-term memory neural networks
Yanrui Jin, Chengjin Qin, Yixiang Huang, et al.
Knowledge-Based Systems (2020) Vol. 193, pp. 105460-105460
Closed Access | Times Cited: 102
Automated heartbeat classification based on deep neural network with multiple input layers
Haotian Shi, Chengjin Qin, Dengyu Xiao, et al.
Knowledge-Based Systems (2019) Vol. 188, pp. 105036-105036
Closed Access | Times Cited: 85
AFCNNet: Automated detection of AF using chirplet transform and deep convolutional bidirectional long short term memory network with ECG signals
Tejas Radhakrishnan, Jay Karhade, Samit Kumar Ghosh, et al.
Computers in Biology and Medicine (2021) Vol. 137, pp. 104783-104783
Open Access | Times Cited: 59
Review of Deep Learning-Based Atrial Fibrillation Detection Studies
Fatma Murat, Ferhat Sadak, Özal Yıldırım, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 21, pp. 11302-11302
Open Access | Times Cited: 59
Convolutional neural network based automatic screening tool for cardiovascular diseases using different intervals of ECG signals
Hao Dai, Hsin-Ginn Hwang, Vincent S. Tseng
Computer Methods and Programs in Biomedicine (2021) Vol. 203, pp. 106035-106035
Closed Access | Times Cited: 57
Deep learning-based automatic segmentation of images in cardiac radiography: A promising challenge
Yucheng Song, Shengbing Ren, Yu Lu, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 220, pp. 106821-106821
Closed Access | Times Cited: 52
Estimating age and gender from electrocardiogram signals: A comprehensive review of the past decade
Mohammed Yusuf Ansari, Marwa Qaraqe, Fatmeh Charafeddine, et al.
Artificial Intelligence in Medicine (2023) Vol. 146, pp. 102690-102690
Open Access | Times Cited: 31
A novel time representation input based on deep learning for ECG classification
Youhe Huang, Hongru Li, Xia Yu
Biomedical Signal Processing and Control (2023) Vol. 83, pp. 104628-104628
Closed Access | Times Cited: 30
Fragment-level classification of ECG arrhythmia using wavelet scattering transform
Sudestna Nahak, Akanksha Pathak, Goutam Saha
Expert Systems with Applications (2023) Vol. 224, pp. 120019-120019
Closed Access | Times Cited: 26
A Deep Learning Approach for Atrial Fibrillation Classification Using Multi-Feature Time Series Data from ECG and PPG
Bader Aldughayfiq, Farzeen Ashfaq, N. Z. Jhanjhi, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2442-2442
Open Access | Times Cited: 22
Towards federated transfer learning in electrocardiogram signal analysis
Wesley Chorney, Haifeng Wang
Computers in Biology and Medicine (2024) Vol. 170, pp. 107984-107984
Closed Access | Times Cited: 8
Automated detection of atrial fibrillation in ECG signals based on wavelet packet transform and correlation function of random process
Jibin Wang, Ping Wang, Suping Wang
Biomedical Signal Processing and Control (2019) Vol. 55, pp. 101662-101662
Closed Access | Times Cited: 61
An incremental learning system for atrial fibrillation detection based on transfer learning and active learning
Haotian Shi, Haoren Wang, Chengjin Qin, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 187, pp. 105219-105219
Closed Access | Times Cited: 61
A novel Domain Adaptive Residual Network for automatic Atrial Fibrillation Detection
Yanrui Jin, Chengjin Qin, Jinlei Liu, et al.
Knowledge-Based Systems (2020) Vol. 203, pp. 106122-106122
Closed Access | Times Cited: 59
Decision support system for arrhythmia prediction using convolutional neural network structure without preprocessing
Hamido Fujita, Dalibor Cimr
Applied Intelligence (2019) Vol. 49, Iss. 9, pp. 3383-3391
Closed Access | Times Cited: 54
Accurate detection of myocardial infarction using non linear features with ECG signals
Chaitra Sridhar, Oh Shu Lih, Jahmunah Vicnesh, et al.
Journal of Ambient Intelligence and Humanized Computing (2020) Vol. 12, Iss. 3, pp. 3227-3244
Closed Access | Times Cited: 54
Detection of Atrial Fibrillation from Single Lead ECG Signal Using Multirate Cosine Filter Bank and Deep Neural Network
Samit Kumar Ghosh, Rajesh Kumar Tripathy, Mario R. Arrieta Paternina, et al.
Journal of Medical Systems (2020) Vol. 44, Iss. 6
Closed Access | Times Cited: 53
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