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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:

Development and Evaluation of a Machine Learning Prediction Model for Small-for-Gestational-Age Births in Women Exposed to Radiation before Pregnancy
Xi Bai, Zhibo Zhou, Yunyun Luo, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 4, pp. 550-550
Open Access | Times Cited: 10

Showing 10 citing articles:

Critical Role of Secondary Organic Aerosol in Urban Atmospheric Visibility Improvement Identified by Machine Learning
Xing Peng, Tingting Xie, Mengxue Tang, et al.
Environmental Science & Technology Letters (2023) Vol. 10, Iss. 11, pp. 976-982
Closed Access | Times Cited: 23
Prediction of Hemorrhagic Complication after Thrombolytic Therapy Based on Multimodal Data from Multiple Centers: An Approach to Machine Learning and System Implementation
Shaoguo Cui, Haojie Song, Huanhuan Ren, et al.
Journal of Personalized Medicine (2022) Vol. 12, Iss. 12, pp. 2052-2052
Open Access | Times Cited: 6
Changes in wintertime visibility across China over 2013–2019 and the drivers: A comprehensive assessment using machine learning method
Lu Chen, Fang Zhang, Jingye Ren, et al.
The Science of The Total Environment (2023) Vol. 912, pp. 169516-169516
Closed Access | Times Cited: 2
Is handling unbalanced datasets for machine learning uplifts system performance?: A case of diabetic prediction
Swati Narwane, Sudhir Sawarkar
Diabetes & Metabolic Syndrome Clinical Research & Reviews (2022) Vol. 16, Iss. 9, pp. 102609-102609
Closed Access | Times Cited: 3
A Systematic Review on the Applications of Machine Learning for Fetal Birth Weight Prediction
Deepak Mane, Jyoti Mante, Anuradha Amar Bakare, et al.
International Journal of Media and Networks (2024) Vol. 2, Iss. 2, pp. 01-12
Open Access
Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy
Xi Bai, Zhibo Zhou, Zeyan Zheng, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access
Post-natal gestational age assessment using targeted metabolites of neonatal heel prick and umbilical cord blood: A GARBH-Ini cohort study from North India
Thirunavukkarasu Ramasamy, Bijo Varughese, Mukesh Kumar Singh, et al.
Journal of Global Health (2024) Vol. 14
Open Access
Low Birth Weight Prediction Model Based on Pre-Pregnancy Information
Kai Wang, Qiaoyun Dai, Xueying Yang, et al.
2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) (2024), pp. 1246-1250
Closed Access
Machine Learning-based Prediction Model for Adverse Pregnancy Outcomes: A Systematic Literature Review
Eka Santy Abdurrahman, Kemal N. Siregar, Rikawarastuti Rikawarastuti, et al.
JURNAL INFO KESEHATAN (2024) Vol. 22, Iss. 3, pp. 532-543
Open Access
A Systematic Review on The Applications of Machine Learning for Fetal Birth Weight Prediction
Deepak Mane, Jyoti Mante, Anuradha Amar Bakare, et al.
Research Square (Research Square) (2023)
Open Access
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