Open Access Helper

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:

Prospects and Pitfalls of Machine Learning in Nutritional Epidemiology
Stefania Russo, Stefano Bonassi
Nutrients (2022) Vol. 14, Iss. 9, pp. 1705-1705
Open Access | Times Cited: 9

Showing 9 citing articles:

A new approach for predicting oil mobilities and unveiling their controlling factors in a lacustrine shale system: Insights from interpretable machine learning model
Enze Wang, Yingxiao Fu, Tonglou Guo, et al.
Fuel (2024) Vol. 379, pp. 132958-132958
Closed Access | Times Cited: 7
Navigating next-gen nutrition care using artificial intelligence-assisted dietary assessment tools—a scoping review of potential applications
Anuja Phalle, Devaki Gokhale
Frontiers in Nutrition (2025) Vol. 12
Open Access
Effects of heavy metal exposure on hypertension: A machine learning modeling approach
Wenxiang Li, Guangyi Huang, Ningning Tang, et al.
Chemosphere (2023) Vol. 337, pp. 139435-139435
Closed Access | Times Cited: 18
Role of Artificial Intelligence in Multinomial Decisions and Preventative Nutrition in Alzheimer's Disease
Ariana Soares Dias Portela, Vrinda Saxena, Eric H. Rosenn, et al.
Molecular Nutrition & Food Research (2024) Vol. 68, Iss. 13
Open Access | Times Cited: 2
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: 2
Bridging Classical Methodologies in Salmonella Investigation with Modern Technologies: A Comprehensive Review
Steven Kitchens, Chengming Wang, Stuart B. Price
Microorganisms (2024) Vol. 12, Iss. 11, pp. 2249-2249
Open Access | Times Cited: 1
Comparison of Nutritional Status Prediction Models of Children Under 5 Years of Age Using Supervised Machine Learning
Mediana Aryuni, Eka Miranda, Meyske Kumbangsila, et al.
Lecture notes in electrical engineering (2023), pp. 265-277
Closed Access | Times Cited: 3
Data-Driven Technology Roadmaps to Identify Potential Technology Opportunities for Hyperuricemia Drugs
Lijie Feng, Weiyu Zhao, Jinfeng Wang, et al.
Pharmaceuticals (2022) Vol. 15, Iss. 11, pp. 1357-1357
Open Access | Times Cited: 6
Dietary intake of potassium, vitamin E, and vitamin C emerges as the most significant predictors of cardiovascular disease risk in adults
Yue Wang, Liyuan Han, Shiliang Ling, et al.
Medicine (2024) Vol. 103, Iss. 32, pp. e39180-e39180
Open Access
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