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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:

Machine learning models for predicting preeclampsia: a systematic review
Amene Ranjbar, Farideh Montazeri, Sepideh Rezaei Ghamsari, et al.
BMC Pregnancy and Childbirth (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 15

Showing 15 citing articles:

Proposing a machine learning-based model for predicting nonreassuring fetal heart
Nasibeh Roozbeh, Farideh Montazeri, Mohammadsadegh Vahidi Farashah, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Machine learning techniques for prediction in pregnancy complicated by autoimmune rheumatic diseases: Applications and challenges
Xiaoshi Zhou, Feifei Cai, Shiran Li, et al.
International Immunopharmacology (2024) Vol. 134, pp. 112238-112238
Open Access | Times Cited: 4
Leveraging Machine Learning to Predict and Assess Disparities in Severe Maternal Morbidity in Maryland
Qingfeng Li, Y. Natalia Alfonso, Carrie Wolfson, et al.
Healthcare (2025) Vol. 13, Iss. 3, pp. 284-284
Open Access
Predicting the Risk of Threatened Abortion via Machine Learning Methods
Zhi Zhu, Na Wei, Junjie Guo, et al.
Research Square (Research Square) (2025)
Closed Access
Prevention of Pre-Eclampsia: Modern Strategies and the Role of Early Screening
Gulzhaina Alipova, Nurgul Ablakimova, Kymbat Tussupkaliyeva, et al.
Journal of Clinical Medicine (2025) Vol. 14, Iss. 9, pp. 2970-2970
Open Access
Current Applications of Artificial Intelligence in Reproductive Medicine (and Predominant OB/GYN and Andrologic Conditions)
Nicholas A Kerna, Taylor M. Nicely, Kingsley Chigozie Iheanacho, et al.
European Journal of Theoretical and Applied Sciences (2025) Vol. 3, Iss. 3, pp. 110-122
Closed Access
Artificial Intelligence Applications in Obstetric Risk Prediction: A Systematic Review of Machine Learning Models for Preeclampsia
Nagla Osman Mohamed Dkeen, Madina Eltayeb Dawelbait Radwan, Israa Ali Alnaw Zumam, et al.
Cureus (2025)
Open Access
Prepregnancy overweight and obesity and the risk of adverse pregnancy outcomes
Fatemeh Abdi, Shiva Alizadeh, Nasibeh Roozbeh, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Prediction of preeclampsia before 11th week of gestation: A secondary analysis of the ASPIRIN trial
Gabriela Capdeville, Andrea Godinez-Medina, Y. Copado, et al.
AJOG Global Reports (2025), pp. 100521-100521
Open Access
Machine learning, advanced data analysis, and a role in pregnancy care? How can we help improve preeclampsia outcomes?
Annemarie Hennessy, Tu Hao Tran, Suraj Narayanan Sasikumar, et al.
Pregnancy Hypertension (2024) Vol. 37, pp. 101137-101137
Open Access | Times Cited: 3
Prevention of Pregnancy Complications Using a Multimodal Lifestyle, Screening, and Medical Model
Jim Parker, Pierre Hofstee, Shaun P. Brennecke
Journal of Clinical Medicine (2024) Vol. 13, Iss. 15, pp. 4344-4344
Open Access | Times Cited: 2
Risk Assessment for Preeclampsia in the Preconception Period Based on Maternal Clinical History via Machine Learning Methods
Yeliz Kaya, Zafer Bütün, Özer Çelik, et al.
Journal of Clinical Medicine (2024) Vol. 14, Iss. 1, pp. 155-155
Open Access | Times Cited: 2
Explainable artificial hydrocarbon networks classifier applied to preeclampsia
Hiram Pönce, Lourdes Martínez-Villaseñor, Antonieta Martínez-Velasco
Information Sciences (2024) Vol. 670, pp. 120556-120556
Open Access
Métodos de inteligência artificial na predição e diagnóstico precoces de complicações na gravidez
Carina Gleice Tabosa Quixabeira, Maria da Conceição Nascimento Gomes, Isabela Oliveira da Silva Flor, et al.
Revista Eletrônica Acervo Saúde (2024) Vol. 24, Iss. 6, pp. e16231-e16231
Open Access
A Review on Machine Learning Deployment Patterns and Key Features in the Prediction of Preeclampsia
L. B. Pedersen, Magdalena Mazur-Milecka, Jacek Rumiński, et al.
Machine Learning and Knowledge Extraction (2024) Vol. 6, Iss. 4, pp. 2515-2569
Open Access
Prediction of Preeclampsia Using Machine Learning: A Systematic Review
Vinayak Malik, Neha Agrawal, Sonal Prasad, et al.
Cureus (2024)
Open Access
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