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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:

Information Theory and Atrial Fibrillation (AF): A Review
Dhani Dharmaprani, Lukah Dykes, Andrew D. McGavigan, et al.
Frontiers in Physiology (2018) Vol. 9
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

Over-fitting suppression training strategies for deep learning-based atrial fibrillation detection
Xiangyu Zhang, Jianqing Li, Zhipeng Cai, et al.
Medical & Biological Engineering & Computing (2021) Vol. 59, Iss. 1, pp. 165-173
Open Access | Times Cited: 48
Fast and Resource Efficient Atrial Fibrillation Detection Framework for Long Term Health Monitoring Devices
Nabasmita Phukan, M. Sabarimalai Manikandan, Ram Bilas Pachori
IEEE Sensors Letters (2024) Vol. 8, Iss. 4, pp. 1-4
Closed Access | Times Cited: 5
Detection of atrial fibrillation from ECG recordings using decision tree ensemble with multi-level features
Minggang Shao, Guangyu Bin, Shuicai Wu, et al.
Physiological Measurement (2018) Vol. 39, Iss. 9, pp. 094008-094008
Closed Access | Times Cited: 42
A New Entropy-Based Atrial Fibrillation Detection Method for Scanning Wearable ECG Recordings
Lina Zhao, Chengyu Liu, Shoushui Wei, et al.
Entropy (2018) Vol. 20, Iss. 12, pp. 904-904
Open Access | Times Cited: 38
Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network
Hua Zhang, Chengyu Liu, Fangfang Tang, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 12
Digital biomarkers and algorithms for detection of atrial fibrillation using surface electrocardiograms: A systematic review
Fons J. Wesselius, Mathijs S. van Schie, Natasja M.S. de Groot, et al.
Computers in Biology and Medicine (2021) Vol. 133, pp. 104404-104404
Open Access | Times Cited: 19
Functional electrographic flow patterns in patients with persistent atrial fibrillation predict outcome of catheter ablation
Tamás Szili-Török, Zsuzsanna Kis, Rohit E. Bhagwandien, et al.
Journal of Cardiovascular Electrophysiology (2021) Vol. 32, Iss. 8, pp. 2148-2158
Open Access | Times Cited: 13
Analysis of the Time-Dependent Behaviors of Atrial Fibrillation with Electrographic Flow Mapping
David E. Haines, Melissa H. Kong, Peter Ruppersberg, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
A Study of R-R Interval Transition Matrix Features for Machine Learning Algorithms in AFib Detection
Sahil Patel, Maximilian Wang, Justin Guo, et al.
Sensors (2023) Vol. 23, Iss. 7, pp. 3700-3700
Open Access | Times Cited: 4
Information theory-based direct causality measure to assess cardiac fibrillation dynamics
Xili Shi, Arunashis Sau, Xinyang Li, et al.
Journal of The Royal Society Interface (2023) Vol. 20, Iss. 207
Open Access | Times Cited: 3
Self-Organized Operational Neural Networks for The Detection of Atrial Fibrillation
Junming Zhang, Hao Dong, Jinfeng Gao, et al.
Journal of Artificial Intelligence and Soft Computing Research (2023) Vol. 14, Iss. 1, pp. 63-75
Open Access | Times Cited: 3
Temporal stability and specificity of high bipolar electrogram entropy regions in sustained atrial fibrillation: Implications for mapping
Dhani Dharmaprani, Andrew D. McGavigan, Darius Chapman, et al.
Journal of Electrocardiology (2018) Vol. 53, pp. 18-27
Closed Access | Times Cited: 8
Reconceptualising Atrial Fibrillation Using Renewal Theory: A Novel Approach to the Assessment of Atrial Fibrillation Dynamics
Jing Quah, Dhani Dharmaprani, Anandaroop Lahiri, et al.
Arrhythmia & Electrophysiology Review (2021) Vol. 10, Iss. 2, pp. 77-84
Open Access | Times Cited: 7
Classification of De novo post-operative and persistent atrial fibrillation using multi-channel ECG recordings
Hanie Moghaddasi, Richard C. Hendriks, A. van Veen, et al.
Computers in Biology and Medicine (2022) Vol. 143, pp. 105270-105270
Open Access | Times Cited: 5
An Efficient Hybrid Methodology for Local Activation Waves Detection under Complex Fractionated Atrial Electrograms of Atrial Fibrillation
Diego Osorio, Aikaterini Vraka, Aurelio Quesada, et al.
Sensors (2022) Vol. 22, Iss. 14, pp. 5345-5345
Open Access | Times Cited: 5
Nonlinear Heart Rate Dynamics Before and After Paroxysmal Atrial Fibrillation Events.
Ting-Wei Liao, Li‐Wei Lo, Yenn‐Jiang Lin, et al.
PubMed (2022) Vol. 38, Iss. 5, pp. 594-600
Closed Access | Times Cited: 5
The application of Lempel-Ziv and Titchener complexity analysis for equine telemetric electrocardiographic recordings
Vadim Alexeenko, James A. Fraser, Alexey Dolgoborodov, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 7
Fundamentals of Cardiac Mapping
Thomas P. Ladas, Alan Sugrue, John Nan, et al.
Cardiac Electrophysiology Clinics (2019) Vol. 11, Iss. 3, pp. 433-448
Closed Access | Times Cited: 7
Dynamical diversity of mitochondrial BK channels located in different cell types
Agata Wawrzkiewicz–Jałowiecka, Paulina Trybek, Łukasz Machura, et al.
Biosystems (2020) Vol. 199, pp. 104310-104310
Closed Access | Times Cited: 6
Fundamentals of arrhythmogenic mechanisms and treatment strategies for equine atrial fibrillation
Antoine Premont, Samantha Balthes, Celia M. Marr, et al.
Equine Veterinary Journal (2021) Vol. 54, Iss. 2, pp. 262-282
Closed Access | Times Cited: 6
Linking the sampling frequency with multiscale entropy to classify mitoBK patch-clamp data
Łukasz Machura, Agata Wawrzkiewicz–Jałowiecka, Piotr Bednarczyk, et al.
Biomedical Signal Processing and Control (2022) Vol. 76, pp. 103680-103680
Closed Access | Times Cited: 4
Multi-scale Entropy Evaluates the Proarrhythmic Condition of Persistent Atrial Fibrillation Patients Predicting Early Failure of Electrical Cardioversion
Eva Cirugeda, Sofı́a Calero, Víctor Manuel Hidalgo, et al.
Entropy (2020) Vol. 22, Iss. 7, pp. 748-748
Open Access | Times Cited: 4
Observable Atrial and Ventricular Fibrillation Episode Durations Are Conformant With a Power Law Based on System Size and Spatial Synchronization
Dhani Dharmaprani, Kathryn Tiver, Sobhan Salari Shahrbabaki, et al.
Circulation Arrhythmia and Electrophysiology (2024) Vol. 17, Iss. 7
Open Access
Predicting Spontaneous Termination of Atrial Fibrillation Based on Analysis of Standard Electrocardiograms: A Systematic Review
Brandon Wadforth, Jing W Goh, Kathryn Tiver, et al.
Annals of Noninvasive Electrocardiology (2024) Vol. 29, Iss. 6
Open Access
mRMEBP: a unified framework for online detection of atrial fibrillation utilizing deep learning
Xiaolin Zhou, Jinyong Zhang, Hui Li, et al.
npj Biomedical Innovations. (2024) Vol. 1, Iss. 1
Open Access
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