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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 algorithms identify demographics, dietary features, and blood biomarkers associated with stroke records
Jundong Liu, Elizabeth L. Chou, Kui Kai Lau, et al.
Journal of the Neurological Sciences (2022) Vol. 440, pp. 120335-120335
Open Access | Times Cited: 8

Showing 8 citing articles:

Predicting Cardiovascular Disease Mortality: Leveraging Machine Learning for Comprehensive Assessment of Health and Nutrition Variables
Agustin Martin‐Morales, Masaki Yamamoto, Mai Inoue, et al.
Nutrients (2023) Vol. 15, Iss. 18, pp. 3937-3937
Open Access | Times Cited: 19
Machine learning to predict stroke risk from routine hospital data: A systematic review
William Heseltine-Carp, Megan Courtman, Daniel Browning, et al.
International Journal of Medical Informatics (2025), pp. 105811-105811
Open Access
Untargeted Metabolomic Analysis of Exhaled Breath Condensate Identifies Disease‐Specific Signatures in Adults With Asthma
Hongfei Zhao, Yujuan Yang, Yan Hao, et al.
Clinical & Experimental Allergy (2025)
Closed Access
An enhanced approach for analyzing the performance of heart stroke prediction with machine learning techniques
Indrani Mishra, Subasish Mohapatra
International Journal of Information Technology (2023) Vol. 15, Iss. 6, pp. 3257-3270
Closed Access | Times Cited: 12
Application of machine learning algorithms to identify people with low bone density
Rongxuan Xu, Yongxing Chen, Zhihan Yao, et al.
Frontiers in Public Health (2024) Vol. 12
Open Access | Times Cited: 3
Machine learning algorithms identify hypokalaemia risk in people with hypertension in the United States National Health and Nutrition Examination Survey 1999–2018
Ziying Lin, Yuen Ting Cheng, Bernard Man Yung Cheung
Annals of Medicine (2023) Vol. 55, Iss. 1
Open Access | Times Cited: 8
Development, validation, and visualization of a novel nomogram to predict stroke risk in patients
Chunxiao Wu, Zhirui Xu, Qizhang Wang, et al.
Frontiers in Aging Neuroscience (2023) Vol. 15
Open Access | Times Cited: 5
Highly Imbalanced Classification of Gout Using Data Resampling and Ensemble Method
Xiaonan Si, Lei Wang, Wenchang Xu, et al.
Algorithms (2024) Vol. 17, Iss. 3, pp. 122-122
Open Access | Times Cited: 1
Exposomics and Cardiovascular Diseases: A Scoping Review of Machine Learning Approaches
Katerina D. Argyri, Ioannis Gallos, Angelos Amditis, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
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