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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.

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Showing 23 citing articles:

Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice
Rohan Khera, Evangelos K. Oikonomou, Girish N. Nadkarni, et al.
Journal of the American College of Cardiology (2024) Vol. 84, Iss. 1, pp. 97-114
Closed Access | Times Cited: 36
Innovation and challenges of artificial intelligence technology in personalized healthcare
Yu-Hao Li, Yulin Li, Mu-Yang Wei, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 26
Artificial intelligence in the management of metabolic disorders: a comprehensive review
A Anwar, Simran Rana, Priya Pathak
Journal of Endocrinological Investigation (2025)
Closed Access | Times Cited: 1
DNA methylation in cardiovascular disease and heart failure: novel prediction models?
Antonella Desiderio, Monica Pastorino, Michele Campitelli, et al.
Clinical Epigenetics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 7
AI-driven evolution of precision population cardiovascular health in cities
Ann Aerts, Michelle A. Williams
Nature Reviews Cardiology (2025)
Closed Access
Application of artificial intelligence technologies in cardiovascular disease detection and management authors
Г. Г. Кутелев, S. A. Parfenov, K. V. Sapozhnikov, et al.
Translational Medicine (2025) Vol. 11, Iss. 6, pp. 562-576
Open Access
The Heart of Transformation: Exploring Artificial Intelligence in Cardiovascular Disease
Mohammed Andaleeb Chowdhury, Rodrigue Rizk, J. Christine Chiu, et al.
Biomedicines (2025) Vol. 13, Iss. 2, pp. 427-427
Open Access
Multi-omics for disease subtyping and classification
Shimaa Sherif, Nagham Nafiz Hendi, Rania Alanany
Elsevier eBooks (2025), pp. 79-134
Closed Access
Artificial intelligence and public health: prospects, hype and challenges
Don Nutbeam, Andrew Milat
Public Health Research & Practice (2025) Vol. 35, Iss. 1
Open Access
Enhanced cardiovascular disease prediction through self-improved Aquila optimized feature selection in quantum neural network & LSTM model
Aman Darolia, Rajender Singh Chhillar, Musaed Alhussein, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 4
The Role of Artificial Intelligence and Machine Learning in Cardiovascular Imaging and Diagnosis
Setareh Reza-Soltani, Laraib Fakhare Alam, Omofolarin Debellotte, et al.
Cureus (2024)
Open Access | Times Cited: 4
Pitfalls in Developing Machine Learning Models for Predicting Cardiovascular Diseases: Challenge and Solutions (Preprint)
Yuqing Cai, Da-Xin Gong, Li-Ying Tang, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e47645-e47645
Open Access | Times Cited: 3
A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction
Achamyeleh Birhanu Teshale, Htet Lin Htun, Mor Vered, et al.
Journal of Medical Systems (2024) Vol. 48, Iss. 1
Open 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
CLEAR guideline for radiomics: Early insights into current reporting practices endorsed by EuSoMII
Burak Koçak, Andrea Ponsiglione, Arnaldo Stanzione, et al.
European Journal of Radiology (2024) Vol. 181, pp. 111788-111788
Closed 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
CSA-DE-LR: enhancing cardiovascular disease diagnosis with a novel hybrid machine learning approach
Beyhan Adanur Dedetürk, Bilge Kagan Dedetürk, Burcu Bakır-Güngör
PeerJ Computer Science (2024) Vol. 10, pp. e2197-e2197
Open Access
Machine learning prediction models for the popularization and dissemination of medical science popularization videos
Nuo Cheng, Xiuling Wang, Yang Mu, et al.
Research Square (Research Square) (2024)
Open Access
Risk Prediction Models for Gastric Cancer: A Scoping Review
Linyu Xu, Jianxia Lyu, Xutong Zheng, et al.
Journal of Multidisciplinary Healthcare (2024) Vol. Volume 17, pp. 4337-4352
Open Access
Algorithms advise, humans decide: the evidential role of the patient preference predictor
Nicholas Makins
Journal of Medical Ethics (2024), pp. jme-110175
Open Access
Evaluating a Novel AI Tool for Automated Measurement of the Aortic Root and Valve in Cardiac Magnetic Resonance Imaging
Jack Parker, James Coey, Tarek Alambrouk, et al.
Cureus (2024)
Open Access
SYSTEMATIC REVIEW: OPPORTUNITIES AND CHALLENGES OF MACHINE LEARNING TECHNIQUES FOR CARDIOVASCULAR DISEASE PREDICTION
Ahmed Qtaishat, Wan Suryani, Wan Suryani Wan Awang
Journal of Southwest Jiaotong University (2024) Vol. 59, Iss. 2
Open Access
Using machine learning to predict acute myocardial infarction and ischemic heart disease in primary care cardiovascular patients
Nèwel Salet, A. Gökdemir, J. Preijde, et al.
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0307099-e0307099
Open Access
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