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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:

Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis
Andreas Karwath, Karina V Bunting, Simrat Gill, et al.
The Lancet (2021) Vol. 398, Iss. 10309, pp. 1427-1435
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Early diagnosis and better rhythm management to improve outcomes in patients with atrial fibrillation: the 8th AFNET/EHRA consensus conference
Renate B. Schnabel, Elena Andreassi Marinelli, Elena Arbelo, et al.
EP Europace (2022) Vol. 25, Iss. 1, pp. 6-27
Open Access | Times Cited: 135
Management of Atrial Fibrillation Across the Spectrum of Heart Failure With Preserved and Reduced Ejection Fraction
Yogesh N.V. Reddy, Barry A. Borlaug, Bernard J. Gersh
Circulation (2022) Vol. 146, Iss. 4, pp. 339-357
Open Access | Times Cited: 78
Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives
Xiaoyu Sun, Yuzhe Yin, Qiwei Yang, et al.
European journal of medical research (2023) Vol. 28, Iss. 1
Open Access | Times Cited: 55
Artificial Intelligence-Based Clinical Decision Support Systems in Cardiovascular Diseases
Serdar Bozyel, Evrim Şimşek, Duygu Koçyiğit Burunkaya, et al.
The Anatolian Journal of Cardiology (2024), pp. 74-86
Open Access | Times Cited: 21
Applying Artificial Intelligence to Wearable Sensor Data to Diagnose and Predict Cardiovascular Disease: A Review
Jiandong Huang, J. Wang, Elaine Ramsey, et al.
Sensors (2022) Vol. 22, Iss. 20, pp. 8002-8002
Open Access | Times Cited: 67
Machine learning in the detection and management of atrial fibrillation
Felix K. Wegner, Lucas Plagwitz, Florian Doldi, et al.
Clinical Research in Cardiology (2022) Vol. 111, Iss. 9, pp. 1010-1017
Open Access | Times Cited: 46
A cardiologist’s guide to machine learning in cardiovascular disease prognosis prediction
Karl‐Patrik Kresoja, Matthias Unterhuber, Rolf Wachter, et al.
Basic Research in Cardiology (2023) Vol. 118, Iss. 1
Open Access | Times Cited: 40
CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research
Dipak Kotecha, Folkert W. Asselbergs, Stephan Achenbach, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 10, pp. e757-e764
Open Access | Times Cited: 39
Artificial intelligence to enhance clinical value across the spectrum of cardiovascular healthcare
Simrat Gill, Andreas Karwath, Hae‐Won Uh, et al.
European Heart Journal (2023) Vol. 44, Iss. 9, pp. 713-725
Open Access | Times Cited: 38
Artificial Intelligence Technologies in Cardiology
Łukasz Ledziński, Grzegorz Grześk
Journal of Cardiovascular Development and Disease (2023) Vol. 10, Iss. 5, pp. 202-202
Open Access | Times Cited: 27
Consumer wearable devices for evaluation of heart rate control using digoxin versus beta-blockers: the RATE-AF randomized trial
Simrat Gill, Andrey Barsky, Xin Guan, et al.
Nature Medicine (2024) Vol. 30, Iss. 7, pp. 2030-2036
Open Access | Times Cited: 9
Machine learning in cardiovascular risk assessment: Towards a precision medicine approach
Yifan Wang, Evmorfia Aivalioti, Kimon Stamatelopoulos, et al.
European Journal of Clinical Investigation (2025) Vol. 55, Iss. S1
Closed Access | Times Cited: 1
CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research
Dipak Kotecha, Folkert W. Asselbergs, Stephan Achenbach, et al.
European Heart Journal (2022) Vol. 43, Iss. 37, pp. 3578-3588
Open Access | Times Cited: 31
Treatment response to spironolactone in patients with heart failure with preserved ejection fraction: a machine learning-based analysis of two randomized controlled trials
Karl‐Patrik Kresoja, Matthias Unterhuber, Rolf Wachter, et al.
EBioMedicine (2023) Vol. 96, pp. 104795-104795
Open Access | Times Cited: 16
Perceptions on artificial intelligence-based decision-making for coexisting multiple long-term health conditions: protocol for a qualitative study with patients and healthcare professionals
Niluka Gunathilaka, Tiffany E. Gooden, Jennifer Cooper, et al.
BMJ Open (2024) Vol. 14, Iss. 2, pp. e077156-e077156
Open Access | Times Cited: 6
CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research
Dipak Kotecha, Folkert W. Asselbergs, Stephan Achenbach, et al.
BMJ (2022), pp. e069048-e069048
Open Access | Times Cited: 22
Systematic reviews of machine learning in healthcare: a literature review
Katarzyna Kolasa, Bisrat Yeshewas Admassu, Malwina Hołownia-Voloskova, et al.
Expert Review of Pharmacoeconomics & Outcomes Research (2023) Vol. 24, Iss. 1, pp. 63-115
Open Access | Times Cited: 14
Heart failure management with β-blockers: can we do better?
Múcio Tavares de Oliveira, Rui Baptista, Sergio Leal, et al.
Current Medical Research and Opinion (2024) Vol. 40, Iss. sup1, pp. 43-54
Open Access | Times Cited: 4
Evaluation of the ABC pathway in patients with atrial fibrillation: A machine learning cluster analysis
Jingyang Wang, Haiyang Bian, Jiang-Shan Tan, et al.
IJC Heart & Vasculature (2025) Vol. 57, pp. 101621-101621
Closed Access
Novel metabolic and inflammatory stratification of overweight/obesity to characterize risks of adverse outcomes: A large population‐based cohort study
Dong Hang, Yingzhou Shi, Yi‐Cheng Ma, et al.
Diabetes Obesity and Metabolism (2025)
Closed Access
Precision phenomapping of pediatric dilated cardiomyopathy using clustering models based on electronic hospital records
Xihang Fu, Zubo Wu, Jiawei Shi, et al.
International Journal of Cardiology (2025), pp. 133127-133127
Closed Access
The Role of Artificial Intelligence in the Prediction, Diagnosis, and Management of Cardiovascular Diseases: A Narrative Review
Maliha Shaikh, Murtaza S Mama, Sri Harika Proddaturi, et al.
Cureus (2025)
Open Access
Identifying distinct clinical clusters in heart failure with mildly reduced ejection fraction
Claartje M.E.M. Meijs, Jasper J. Brugts, Lars H. Lund, et al.
International Journal of Cardiology (2023) Vol. 386, pp. 83-90
Open Access | Times Cited: 11
Discovering Distinct Phenotypical Clusters in Heart Failure Across the Ejection Fraction Spectrum: a Systematic Review
Claartje M.E.M. Meijs, M. Louis Handoko, Gianluigi Savarese, et al.
Current Heart Failure Reports (2023) Vol. 20, Iss. 5, pp. 333-349
Open Access | Times Cited: 11
Novel Artificial Intelligence Applications in Cardiology: Current Landscape, Limitations, and the Road to Real-World Applications
Élodie Labrecque Langlais, Pascal Thériault-Lauzier, Guillaume Marquis‐Gravel, et al.
Journal of Cardiovascular Translational Research (2022) Vol. 16, Iss. 3, pp. 513-525
Closed Access | Times Cited: 18
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