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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 11 citing articles:

Machine learning based differential diagnosis of schizophrenia, major depression disorder and bipolar disorder using structural magnetic resonance imaging
Peiyu Cao, Runda Li, Yuting Li, et al.
Journal of Affective Disorders (2025) Vol. 383, pp. 20-31
Closed Access
Improving Lung Cancer Risk Prediction Using Machine Learning: A Comparative Analysis of Stacking Models and Traditional Approaches
Huakang Tu, Yunfeng Zhao, Jiameng Cui, et al.
Cancers (2025) Vol. 17, Iss. 10, pp. 1651-1651
Open Access
Prediction of adolescent suicidal ideation after the COVID-19 pandemic: A nationwide survey of a representative sample of Korea
Haewon Byeon
Frontiers in Pediatrics (2022) Vol. 10
Open Access | Times Cited: 14
Construction and validation of machine learning algorithm for predicting depression among home-quarantined individuals during the large-scale COVID-19 outbreak: based on Adaboost model
Yiwei Zhou, Zejie Zhang, Qin Li, et al.
BMC Psychology (2024) Vol. 12, Iss. 1
Open Access | Times Cited: 1
Predicting sarcopenia risk in stroke patients: a comprehensive nomogram incorporating demographic, anthropometric, and biochemical indicators
Yuehua Pu, Ying Wang, Huan Wang, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 1
Predicting South Korean adolescents vulnerable to obesity after the COVID-19 pandemic using categorical boosting and shapley additive explanation values: A population-based cross-sectional survey
Haewon Byeon
Frontiers in Pediatrics (2022) Vol. 10
Open Access | Times Cited: 6
Influence of the COVID-19 Pandemic on the Subjective Life Satisfaction of South Korean Adults: Bayesian Nomogram Approach
Haewon Byeon
Diagnostics (2022) Vol. 12, Iss. 3, pp. 761-761
Open Access | Times Cited: 5
Lifestyle factors and other predictors of common mental disorders in diagnostic machine learning studies: A systematic review
Emma Todd, Rebecca Orr, Elizabeth Gamage, et al.
Computers in Biology and Medicine (2024) Vol. 185, pp. 109521-109521
Open Access
Karar Ağacı ve Kural Tümevarımı ile Eğitsel Veri Madenciliği: SAÜ İLİTAM Örneği
Deniz Demircioğlu Diren, Mehmet Barış Horzum
Pamukkale University Journal of Education (2024)
Open Access
Enhancing Depression Detection: A Stacked Ensemble Model with Feature Selection and RF Feature Importance Analysis Using NHANES Data
Annapoorani Selvaraj, Lakshmi Mohandoss
Applied Sciences (2024) Vol. 14, Iss. 16, pp. 7366-7366
Open Access
Predicting South Korea adolescents vulnerable to depressive disorder using Bayesian nomogram: A community-based cross-sectional study
Haewon Byeon
World Journal of Psychiatry (2022) Vol. 12, Iss. 7, pp. 915-928
Open Access | Times Cited: 2
Developing a nomogram for predicting depression in diabetic patients after COVID-19 using machine learning
Haewon Byeon
Frontiers in Public Health (2023) Vol. 11
Open Access
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