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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:

Routinely collected antenatal data for longitudinal prediction of preeclampsia in nulliparous women: a population-based study
Anna Sandström, Jonathan M. Snowden, Matteo Bottai, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 10

Showing 10 citing articles:

Preeclampsia Prediction Using Machine Learning and Polygenic Risk Scores From Clinical and Genetic Risk Factors in Early and Late Pregnancies
Vesela Kovacheva, Braden W Eberhard, Raphael Y. Cohen, et al.
Hypertension (2023) Vol. 81, Iss. 2, pp. 264-272
Open Access | Times Cited: 21
Prevalence and incidence of transfusion‐transmissible infections among blood donors in Malawi: A population‐level study
Emmanuel Singogo, Maganizo Chagomerana, Collin Van Ryn, et al.
Transfusion Medicine (2023) Vol. 33, Iss. 6, pp. 483-496
Open Access | Times Cited: 7
An Interpretable Longitudinal Preeclampsia Risk Prediction Using Machine Learning
Braden W Eberhard, Raphael Y. Cohen, John Rigoni, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 6
The Stockholm–Gotland perinatal cohort—A population‐based cohort including longitudinal data throughout pregnancy and the postpartum period
Kari Johansson, Michaela Granfors, Gunnar Petersson, et al.
Paediatric and Perinatal Epidemiology (2022) Vol. 37, Iss. 4, pp. 276-286
Open Access | Times Cited: 10
Prediction of pre-eclampsia with machine learning approaches: Leveraging important information from routinely collected data
Sofonyas Abebaw Tiruneh, Daniel L. Rolnik, Helena Teede, et al.
International Journal of Medical Informatics (2024) Vol. 192, pp. 105645-105645
Open Access | Times Cited: 1
Development and evaluation of a nomogram for adverse outcomes of preeclampsia in Chinese pregnant women
Jiangyuan Zheng, Li Zhang, Yang Zhou, et al.
BMC Pregnancy and Childbirth (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 6
Prediction of Preeclampsia from Clinical and Genetic Risk Factors in Early and Late Pregnancy Using Machine Learning and Polygenic Risk Scores
Vesela Kovacheva, Braden W Eberhard, Raphael Y. Cohen, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Chapter 9: Preeclampsia and eclampsia: enhanced detection and treatment for morbidity reduction
Vesela Kovacheva, S Venkatachalam, Charles Pfister, et al.
Best Practice & Research Clinical Anaesthesiology (2024) Vol. 38, Iss. 3, pp. 246-256
Closed Access
Association between systolic blood pressure course and outcomes after stroke thrombectomy
Marius Matusevicius, Charith Cooray, Staffan Holmin, et al.
BMJ Neurology Open (2021) Vol. 3, Iss. 2, pp. e000183-e000183
Open Access | Times Cited: 2
Histopathological Aspects of Placental Lesions in Mild and Severe Pre-Eclampsia in a Population of Cameroonian Women
Félix Essiben, Ayissi Gregory, Étienne Belinga, et al.
Open Journal of Obstetrics and Gynecology (2022) Vol. 12, Iss. 02, pp. 154-168
Open Access
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