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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:

Machine Learning and the Conundrum of Stroke Risk Prediction
Yaacoub Chahine, Matthew J Magoon, Bahetihazi Maidu, et al.
Arrhythmia & Electrophysiology Review (2023) Vol. 12
Open Access | Times Cited: 18

Showing 18 citing articles:

Reduced-order models of wall shear stress patterns in the left atrial appendage from a data-augmented atrial database
Jorge Dueñas-Pamplona, Sergio Rodríguez-Aparicio, Alejandro Gonzalo, et al.
Applied Mathematical Modelling (2024) Vol. 130, pp. 713-727
Open Access | Times Cited: 5
Integrating AI-driven wearable devices and biometric data into stroke risk assessment: A review of opportunities and challenges
David B. Olawade, Nicholas Aderinto, Aanuoluwapo Clement David-Olawade, et al.
Clinical Neurology and Neurosurgery (2024) Vol. 249, pp. 108689-108689
Open Access | Times Cited: 4
Urban and rural disparities in stroke prediction using machine learning among Chinese older adults
Jingjing Zhu, Luotao Lin, Lei Si, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Choroidal thickness as predictor of subclinical carotid atherosclerosis in adults with type 1 diabetes
Esmeralda Castelblanco, Ignacio Salvador-Miras, Marc Carbonell, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Development of explainable artificial intelligence based machine learning model for predicting 30-day hospital readmission after renal transplantation
Nasser Alnazari, Omar Ibrahim Alanazi, M.B. Al-Osaimi, et al.
BMC Nephrology (2025) Vol. 26, Iss. 1
Open Access
Atrial fibrillation substrate and impaired left atrial function: a cardiac MRI study
Yaacoub Chahine, Nadia Chamoun, Ahmad Kassar, et al.
EP Europace (2024) Vol. 26, Iss. 11
Open Access | Times Cited: 3
Super-resolution left ventricular flow and pressure mapping by Navier–Stokes-informed neural networks
Bahetihazi Maidu, Pablo Martínez‐Legazpi, Manuel Guerrero‐Hurtado, et al.
Computers in Biology and Medicine (2024) Vol. 185, pp. 109476-109476
Closed Access | Times Cited: 3
Machine learning based prediction models for cardiovascular disease risk using electronic health records data: systematic review and meta-analysis
Tiedong Liu, Andrew J. Krentz, Lei Lü, et al.
European Heart Journal - Digital Health (2024) Vol. 6, Iss. 1, pp. 7-22
Open Access | Times Cited: 2
The most efficient machine learning algorithms in stroke prediction: A systematic review
Farkhondeh Asadi, Milad Rahimi, Amir Hossein Daeechini, et al.
Health Science Reports (2024) Vol. 7, Iss. 10
Open Access | Times Cited: 2
Personalized biomechanical insights in atrial fibrillation: opportunities & challenges
Åshild Telle, Clarissa Bargellini, Yaacoub Chahine, et al.
Expert Review of Cardiovascular Therapy (2023) Vol. 21, Iss. 11, pp. 817-837
Closed Access | Times Cited: 5
Computational Medicine: What Electrophysiologists Should Know to Stay Ahead of the Curve
Matthew J Magoon, Babak Nazer, Nazem Akoum, et al.
Current Cardiology Reports (2024)
Closed Access | Times Cited: 1
Stroke Dataset Modeling: Comparative Study of Machine Learning Classification Methods
Kalina Kitova, Ivan Ivanov, Vincent J. Hooper
Algorithms (2024) Vol. 17, Iss. 12, pp. 571-571
Open Access | Times Cited: 1
Machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients based on multimodal echocardiographic parameters
Decai Zeng, Shuai Chang, Xiaofeng Zhang, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Super-resolution Left Ventricular Flow and Pressure Mapping by Navier-Stokes-Informed Neural Networks
Bahetihazi Maidu, Pablo Martínez‐Legazpi, Manuel Guerrero‐Hurtado, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Association between deep neural network-derived electrocardiographic-age and incident stroke
Robert Leung, Biqi Wang, Matthew Gottbrecht, et al.
Frontiers in Cardiovascular Medicine (2024) Vol. 11
Open Access
Ischemic stroke and the emerging role of left atrial function
Bjørn Strøier Larsen, Tor Biering‐Sørensen, Flemming Javier Olsen
Expert Review of Cardiovascular Therapy (2024) Vol. 22, Iss. 7, pp. 289-300
Open Access
From Imputation to Prediction: A Comprehensive Machine Learning Pipeline for Stroke Risk Analysis
S. Padmakala, A. Chandrasekar
2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (2024), pp. 1-7
Closed Access
Development and Validation of an Interpretable Risk Prediction Model for Perioperative Ischemic Stroke in Noncardiac, Nonvascular, and Nonneurosurgical Patients: A Retrospective Study
Xuhui Cong, Xuli Zou, Ruilou Zhu, et al.
Research Square (Research Square) (2024)
Open Access
Adaptive prior image constrained total generalized variation for low-dose dynamic cerebral perfusion CT reconstruction
Shanzhou Niu, Shuo Li, Shuyan Huang, et al.
Journal of X-Ray Science and Technology (2024), pp. 1-19
Closed Access
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