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 20 citing articles:

Advanced mass spectrometric and spectroscopic methods coupled with machine learning for in vitro diagnosis
Xiaonan Chen, Weikang Shu, Liang Zhao, et al.
View (2022) Vol. 4, Iss. 1
Open Access | Times Cited: 54

Machine learning approaches for biomarker discovery to predict large-artery atherosclerosis
Ting-Hsuan Sun, Chia‐Chun Wang, Ya-Lun Wu, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 17

Understanding complex functional wiring patterns in major depressive disorder through brain functional connectome
Zhiyun Yang, Lingyu Jian, Hui Qiu, et al.
Translational Psychiatry (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 38

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures
Ran Zheng, Rui Su, Yusi Fan, et al.
Analytical Chemistry (2024) Vol. 96, Iss. 21, pp. 8772-8781
Closed Access | Times Cited: 5

Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice
Mingzhi Lin, Jiuqi Guo, Zhilin Gu, et al.
Journal of Translational Medicine (2025) Vol. 23, Iss. 1
Open Access

Multinomial machine learning identifies independent biomarkers by integrated metabolic analysis of acute coronary syndrome
Meijiao Fu, Ruhua He, Zhihan Zhang, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 10

Urine biomarkers discovery by metabolomics and machine learning for Parkinson's disease diagnoses
Xiaoxiao Wang, Xinran Hao, Jie Yan, et al.
Chinese Chemical Letters (2023) Vol. 34, Iss. 10, pp. 108230-108230
Open Access | Times Cited: 7

Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management
Shanshan Nie, Shan Zhang, Yuhang Zhao, et al.
Advances in Therapy (2024) Vol. 42, Iss. 2, pp. 636-665
Closed Access | Times Cited: 2

Machine Learning Algorithm to Predict Obstructive Coronary Artery Disease: Insights from the CorLipid Trial
Eleftherios Panteris, Olga Deda, Αndreas S. Papazoglou, et al.
Metabolites (2022) Vol. 12, Iss. 9, pp. 816-816
Open Access | Times Cited: 10

A novel lightweight deep learning fall detection system based on global-local attention and channel feature augmentation
Yuyang Sha, Xiaobing Zhai, Junrong Li, et al.
Interdisciplinary Nursing Research (2023) Vol. 2, Iss. 2, pp. 68-75
Open Access | Times Cited: 4

A multiple-metabolites model to predict preliminary renal injury induced by iodixanol based on UHPLC/Q-Orbitrap-MS and 1H-NMR
Liying Cheng, Liming Wang, Biying Chen, et al.
Metabolomics (2022) Vol. 18, Iss. 11
Closed Access | Times Cited: 5

Perturbations in cardiac metabolism in a human model of acute myocardial ischaemia
Sanoj Chacko, Mamas A. Mamas, Magdi El‐Omar, et al.
Metabolomics (2021) Vol. 17, Iss. 9
Open Access | Times Cited: 7

Progress in the Metabolomics of Acute Coronary Syndrome
Zhang Fu, Bo Li, Hongling Su, et al.
Reviews in Cardiovascular Medicine (2023) Vol. 24, Iss. 7
Open Access | Times Cited: 2

Artificial intelligence on interventional cardiology
Chayakrit Krittanawong, Scott Kaplin, Sanjeev Sharma
Elsevier eBooks (2023), pp. 51-63
Closed Access | Times Cited: 2

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