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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:

The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics
Feng-Hsu Wang, Chih‐Ming Lin
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 24, pp. 9288-9288
Open Access | Times Cited: 8

Showing 8 citing articles:

Machine learning-based predictive model for prevention of metabolic syndrome
Hyun-Seok Shin, Simon Shim, Sejong Oh
PLoS ONE (2023) Vol. 18, Iss. 6, pp. e0286635-e0286635
Open Access | Times Cited: 15
Predicting metabolic syndrome: Machine learning techniques for improved preventive medicine
Orit Goldman, Ofir Ben‐Assuli, Shimon Ababa, et al.
Health Informatics Journal (2025) Vol. 31, Iss. 1
Open Access
Metabolic syndrome prediction model using Bayesian optimization and XGBoost based on traditional Chinese medicine features
Jianhua Zheng, Z. Zhang, Jinhe Wang, et al.
Heliyon (2023) Vol. 9, Iss. 12, pp. e22727-e22727
Open Access | Times Cited: 8
Identifying Metabolic Syndrome Easily and Cost Effectively Using Non-Invasive Methods with Machine Learning Models
Wei Xu, Zikai Zhang, Kerong Hu, et al.
Diabetes Metabolic Syndrome and Obesity (2023) Vol. Volume 16, pp. 2141-2151
Open Access | Times Cited: 4
Revolutionizing Metabolic Syndrome Detection and Classification with State-of-the-Art Machine Learning Techniques
Nandini Modi, Yogesh Kumar
2022 IEEE 7th International conference for Convergence in Technology (I2CT) (2024)
Closed Access | Times Cited: 1
Classical and Neural Network Machine Learning to Determine the Risk of Marijuana Use
Laura Zoboroski, Torrey Wagner, Brent Langhals
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 14, pp. 7466-7466
Open Access | Times Cited: 7
Artificial Neural Networks to Predict Metabolic Syndrome in Adolescents
Antônio Luís Rodrigues Costa Júnior, Ana Karina Teixeira da Cunha França, Elisângela dos Santos, et al.
(2024)
Open Access
Artificial Neural Networks to Predict Metabolic Syndrome without Invasive Methods in Adolescents
Antônio Luís Rodrigues Costa Júnior, Ana Karina Teixeira da Cunha França, Elisângela dos Santos, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 19, pp. 5914-5914
Open Access
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