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:

Using machine learning to improve our understanding of COVID-19 infection in children
Shraddha Piparia, Andrew Defante, Kelan G. Tantisira, et al.
PLoS ONE (2023) Vol. 18, Iss. 2, pp. e0281666-e0281666
Open Access | Times Cited: 9

Showing 9 citing articles:

Medical imaging: A Critical Review on X-ray Imaging for the Detection of Infection
Egwonor Loveth Irede, Omowunmi Rebecca Aworinde, Ogunnaike Korede Lekan, et al.
Deleted Journal (2024)
Closed Access | Times Cited: 6
Environmentally friendly PAEs alternatives with desired synthesizability by machine learning methods
Pengfei Qiu, Hao Yang
Journal of environmental chemical engineering (2025), pp. 115946-115946
Closed Access
Environmentally friendly PAEs alternatives with desired synthesizability by in silico methods
Hao Yang, Qing Li, Wu Yang, et al.
Journal of Cleaner Production (2023) Vol. 424, pp. 138925-138925
Closed Access | Times Cited: 8
Using machine learning to identify patient characteristics to predict mortality of in-patients with COVID-19 in South Florida
Debarshi Datta, Safiya George Dalmida, Laurie A. Martinez, et al.
Frontiers in Digital Health (2023) Vol. 5
Open Access | Times Cited: 6
A novel deep learning-based approach for prediction of neonatal respiratory disorders from chest X-ray images
Ayşe Yildirim, Murat Canayaz
Journal of Applied Biomedicine (2023) Vol. 43, Iss. 4, pp. 635-655
Closed Access | Times Cited: 6
Evaluating and Reducing Subgroup Disparity in AI Models: An Analysis of Pediatric COVID-19 Test Outcomes
Alexander Libin, Jonah T. Treitler, Tadas Vasaitis, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Prediction of COVID-19 Severity and Mortality in Hospitalized Children Using Machine Learning Tree-based Classifiers
Mehran Karimi, Zahra Nafei, Farimah Shamsi, et al.
Research Square (Research Square) (2024)
Open Access
Evaluating and Reducing Subgroup Disparity in AI Models Predicting Pediatric COVID-19 Test Outcomes
Alexander Libin, Jonah T. Treitler, Tadas Vasaitis, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 5033-5042
Closed Access
Evaluating and Reducing AI Model Group Disparity: An Analysis of COVID Test Outcomes in Children
Alexander Libin, Jonah T. Treitler, Yijun Shao
2021 International Conference on Computational Science and Computational Intelligence (CSCI) (2023), pp. 1511-1513
Closed Access
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