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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:

Multi-parametric Analysis for Atrial Fibrillation Classification in the ECG
Ivaylo Christov, Vessela Krasteva, Iana Simova, et al.
Computing in cardiology (2017)
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Arrhythmia Recognition and Classification Using Combined Parametric and Visual Pattern Features of ECG Morphology
Hui Yang, Zhiqiang Wei
IEEE Access (2020) Vol. 8, pp. 47103-47117
Open Access | Times Cited: 76
Application of Dense Neural Networks for Detection of Atrial Fibrillation and Ranking of Augmented ECG Feature Set
Vessela Krasteva, Ivaylo Christov, Stefan Naydenov, et al.
Sensors (2021) Vol. 21, Iss. 20, pp. 6848-6848
Open Access | Times Cited: 31
Survey on atrial fibrillation detection from a single-lead ECG wave for Internet of Medical Things
Yu Liu, Junxin Chen, Nan Bao, et al.
Computer Communications (2021) Vol. 178, pp. 245-258
Closed Access | Times Cited: 29
Automatic classification of atrial fibrillation from short single-lead ECG recordings using a Hybrid Approach of Dual Support Vector Machine
Gamal G. N. Geweid, Jiande D. Z. Chen
Expert Systems with Applications (2022) Vol. 198, pp. 116848-116848
Closed Access | Times Cited: 22
Ranking of the most reliable beat morphology and heart rate variability features for the detection of atrial fibrillation in short single-lead ECG
Ivaylo Christov, Vessela Krasteva, Iana Simova, et al.
Physiological Measurement (2018) Vol. 39, Iss. 9, pp. 094005-094005
Closed Access | Times Cited: 28
A Novel Approach for Heart Ventricular and Atrial Abnormalities Detection via an Ensemble Classification Algorithm Based on ECG Morphological Features
Hui Yang, Zhiqiang Wei
IEEE Access (2021) Vol. 9, pp. 54757-54774
Open Access | Times Cited: 16
A Comparative Analysis of 2D Deep CNN Models for Arrhythmia Detection Using STFT-Based Long Duration ECG Spectrogram
Tabassum Islam Toma, Sunwoong Choi
2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN) (2022), pp. 483-488
Closed Access | Times Cited: 11
In-Distribution and Out-of-Distribution Self-Supervised ECG Representation Learning for Arrhythmia Detection
Sahar Soltanieh, Javad Hashemi, Ali Etemad
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 28, Iss. 2, pp. 789-800
Open Access | Times Cited: 6
Atrial Fibrillation Classification and Prediction Explanation using Transformer Neural Network
Deepankar Nankani, Rashmi Dutta Baruah
2022 International Joint Conference on Neural Networks (IJCNN) (2022), pp. 01-08
Closed Access | Times Cited: 8
Atrial fibrillation detection in outpatient electrocardiogram monitoring: An algorithmic crowdsourcing approach
Ali Bahrami Rad, Conner Galloway, Daniel Treiman, et al.
PLoS ONE (2021) Vol. 16, Iss. 11, pp. e0259916-e0259916
Open Access | Times Cited: 10
Automatic Detection of Atrial Fibrillation from ECG Signal Using Hybrid Deep Learning Techniques
Saroj Kumar Pandey, Gaurav Kumar, Shubham Shukla, et al.
Journal of Sensors (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 6
Machine Learning Based Decision Support System for Atrial Fibrillation Detection using Electrocardiogram
Shrikanth Rao S.K, Roshan Joy Martis
(2020), pp. 263-266
Closed Access | Times Cited: 8
Classification of Arrhythmia in Time Series ECG Signals Using Image Encoding And Convolutional Neural Networks
K. Vandith Sreenivas, M. Ganesan, R Lavanya
(2021), pp. 1-6
Closed Access | Times Cited: 8
An End-to-End framework for automatic detection of Atrial Fibrillation using Deep Residual Learning
Deepankar Nankani, Rashmi Dutta Baruah
TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON) (2019), pp. 690-695
Closed Access | Times Cited: 7
Event-based Neural Network for ECG Classification with Delta Encoding and Early Stopping
Matthias Jobst, Chen Liu, Johannes Partzsch, et al.
(2020)
Closed Access | Times Cited: 7
2D Image-Based Atrial Fibrillation Classification
Felipe Meneguitti Dias, Nelson Samesima, Adèle H. Ribeiro, et al.
2021 Computing in Cardiology (CinC) (2021) Vol. 83, pp. 1-4
Closed Access | Times Cited: 6
Classification of Arrhythmia Based on Machine Learning Algorithms Using ECG Signals
P. Varalakshmi, Atshaya P. Sankaran
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (2022), pp. 1-7
Closed Access | Times Cited: 4
A Prototype Framework Design for Assisting the Detection of Atrial Fibrillation Using a Generic Low-Cost Biomedical Sensor
Jesús Pérez-Valero, Antonio-Javier García-Sánchez, Manuel Ruiz Marín, et al.
Sensors (2020) Vol. 20, Iss. 3, pp. 896-896
Open Access | Times Cited: 5
Enhancing Interpretability in Image-Based Ecg Exams for Atrial Fibrillation Classification Using Deep Learning
Estela Ribeiro, Felipe Meneguitti Dias, José Eduardo Krieger, et al.
(2024)
Closed Access
Multi-type Arrhythmia Classification: Assessment of the Potential of Time and Frequency Domain Features and Different Classifiers
Irena Jekova, G. Bortolan, Todor Stoyanov, et al.
International Journal Bioautomation (2020) Vol. 24, Iss. 2, pp. 153-172
Open Access | Times Cited: 3
Atrial fibrillation detection using Poincare geometry and heart beat intervals
Shrikanth Rao S.K, Maheshkumar H. Kolekar, Roshan Joy Martis
Expert Systems (2023) Vol. 40, Iss. 7
Closed Access | Times Cited: 1
In-Distribution and Out-of-Distribution Self-supervised ECG Representation Learning for Arrhythmia Detection
Sahar Soltanieh, Javad Hashemi, Ali Etemad
arXiv (Cornell University) (2023)
Open Access | Times Cited: 1
Addressing the Challenge of Data Heterogeneity Using a Homogeneous Feature Vector Representation: A Study Using Time Series and Cardiovascular Disease Classification
Hanadi Aldosari, Frans Coenen, Gregory Y.H. Lip, et al.
Lecture notes in computer science (2021), pp. 254-266
Closed Access | Times Cited: 3
Atrial Fibrillation Discrimination for Real-Time ECG Monitoring Based On QT Interval Variation
Ekta Soni, Arpita Nagpal, Khyati Chopra
Indian Journal of Science and Technology (2022) Vol. 15, Iss. 17, pp. 767-777
Open Access | Times Cited: 1
Clustered Standard Deviation and Its Benefit to Identify Atrial Fibrillation
Filip Plešinger, Ivo Viščor, Petr Nejedlý, et al.
(2019), pp. 1-4
Closed Access
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