
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:
Novel electronic health records applied for prediction of pre-eclampsia: Machine-learning algorithms
Yixin Li, Xiaoping Shen, Chao Yang, et al.
Pregnancy Hypertension (2021) Vol. 26, pp. 102-109
Open Access | Times Cited: 29
Yixin Li, Xiaoping Shen, Chao Yang, et al.
Pregnancy Hypertension (2021) Vol. 26, pp. 102-109
Open Access | Times Cited: 29
Showing 1-25 of 29 citing articles:
Prediction of Preeclampsia Using Machine Learning and Deep Learning Models: A Review
Sumayh S. Aljameel, Manar Alzahrani, Reem Almusharraf, et al.
Big Data and Cognitive Computing (2023) Vol. 7, Iss. 1, pp. 32-32
Open Access | Times Cited: 25
Sumayh S. Aljameel, Manar Alzahrani, Reem Almusharraf, et al.
Big Data and Cognitive Computing (2023) Vol. 7, Iss. 1, pp. 32-32
Open Access | Times Cited: 25
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: 24
Vesela Kovacheva, Braden W Eberhard, Raphael Y. Cohen, et al.
Hypertension (2023) Vol. 81, Iss. 2, pp. 264-272
Open Access | Times Cited: 24
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
Amene Ranjbar, Farideh Montazeri, Sepideh Rezaei Ghamsari, et al.
BMC Pregnancy and Childbirth (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 15
The role of cell-free DNA biomarkers and patient data in the early prediction of preeclampsia: an artificial intelligence model
Asma Khalil, Giovanni Bellesia, Mary E. Norton, et al.
American Journal of Obstetrics and Gynecology (2024) Vol. 231, Iss. 5, pp. 554.e1-554.e18
Closed Access | Times Cited: 9
Asma Khalil, Giovanni Bellesia, Mary E. Norton, et al.
American Journal of Obstetrics and Gynecology (2024) Vol. 231, Iss. 5, pp. 554.e1-554.e18
Closed Access | Times Cited: 9
Artificial Intelligence and Machine Learning in Preeclampsia
Anita T. Layton
Arteriosclerosis Thrombosis and Vascular Biology (2025)
Closed Access | Times Cited: 1
Anita T. Layton
Arteriosclerosis Thrombosis and Vascular Biology (2025)
Closed Access | Times Cited: 1
Development of a prediction model on preeclampsia using machine learning-based method: a retrospective cohort study in China
Mengyuan Liu, Xiaofeng Yang, Guolu Chen, et al.
Frontiers in Physiology (2022) Vol. 13
Open Access | Times Cited: 30
Mengyuan Liu, Xiaofeng Yang, Guolu Chen, et al.
Frontiers in Physiology (2022) Vol. 13
Open Access | Times Cited: 30
Machine Learning Algorithms Versus Classical Regression Models in Pre-Eclampsia Prediction: A Systematic Review
Sofonyas Abebaw Tiruneh, Tra Thuan Thanh Vu, Daniel L. Rolnik, et al.
Current Hypertension Reports (2024) Vol. 26, Iss. 7, pp. 309-323
Open Access | Times Cited: 7
Sofonyas Abebaw Tiruneh, Tra Thuan Thanh Vu, Daniel L. Rolnik, et al.
Current Hypertension Reports (2024) Vol. 26, Iss. 7, pp. 309-323
Open Access | Times Cited: 7
Predicting intensive care need in women with preeclampsia using machine learning – a pilot study
Camilla Edvinsson, Ola Björnsson, Lena Erlandsson, et al.
Hypertension in Pregnancy (2024) Vol. 43, Iss. 1
Open Access | Times Cited: 6
Camilla Edvinsson, Ola Björnsson, Lena Erlandsson, et al.
Hypertension in Pregnancy (2024) Vol. 43, Iss. 1
Open Access | Times Cited: 6
An imbalance-aware deep neural network for early prediction of preeclampsia
R. Avery Bennett, Zuber D. Mulla, Pavan Parikh, et al.
PLoS ONE (2022) Vol. 17, Iss. 4, pp. e0266042-e0266042
Open Access | Times Cited: 17
R. Avery Bennett, Zuber D. Mulla, Pavan Parikh, et al.
PLoS ONE (2022) Vol. 17, Iss. 4, pp. e0266042-e0266042
Open Access | Times Cited: 17
Noninvasive early prediction of preeclampsia in pregnancy using retinal vascular features
Yuxuan Wu, Lixia Shen, Lanqin Zhao, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open Access
Yuxuan Wu, Lixia Shen, Lanqin Zhao, et al.
npj Digital Medicine (2025) Vol. 8, Iss. 1
Open 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
Gulzhaina Alipova, Nurgul Ablakimova, Kymbat Tussupkaliyeva, et al.
Journal of Clinical Medicine (2025) Vol. 14, Iss. 9, pp. 2970-2970
Open 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
Nagla Osman Mohamed Dkeen, Madina Eltayeb Dawelbait Radwan, Israa Ali Alnaw Zumam, et al.
Cureus (2025)
Open Access
Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms
Yixin Li, Yichen Liu, Mei Wang, et al.
Archives of Gynecology and Obstetrics (2023) Vol. 309, Iss. 6, pp. 2557-2566
Closed Access | Times Cited: 7
Yixin Li, Yichen Liu, Mei Wang, et al.
Archives of Gynecology and Obstetrics (2023) Vol. 309, Iss. 6, pp. 2557-2566
Closed Access | Times Cited: 7
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
Jim Parker, Pierre Hofstee, Shaun P. Brennecke
Journal of Clinical Medicine (2024) Vol. 13, Iss. 15, pp. 4344-4344
Open Access | Times Cited: 2
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: 2
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: 2
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.
(2024)
Open Access | Times Cited: 1
L. B. Pedersen, Magdalena Mazur-Milecka, Jacek Rumiński, et al.
(2024)
Open Access | Times Cited: 1
Early Prediction of Hypertensive Disorders of Pregnancy Using Machine Learning and Medical Records from the First and Second Trimesters
Seyedeh Somayyeh Mousavi, Kim Tierney, Chad Robichaux, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Seyedeh Somayyeh Mousavi, Kim Tierney, Chad Robichaux, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
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
Vesela Kovacheva, Braden W Eberhard, Raphael Y. Cohen, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Predicting Preeclampsia Using Principal Component Analysis and Decision Tree Classifier
Farida Musa, Rajesh Prasad
Current Women s Health Reviews (2023) Vol. 20, Iss. 2
Closed Access | Times Cited: 2
Farida Musa, Rajesh Prasad
Current Women s Health Reviews (2023) Vol. 20, Iss. 2
Closed 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
Hiram Pönce, Lourdes Martínez-Villaseñor, Antonieta Martínez-Velasco
Information Sciences (2024) Vol. 670, pp. 120556-120556
Open Access
Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid (MHAVH) Model
Hina Naz, Zuping Zhang, Mohammed Al‐Habib, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 2, pp. 2673-2696
Open Access
Hina Naz, Zuping Zhang, Mohammed Al‐Habib, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 2, pp. 2673-2696
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
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
Using machine learning to predict the risk of developing hypertensive disorders of pregnancy using a contemporary nulliparous cohort
Jonathan S. Schor, Adesh Kadambi, Isabel Fulcher, et al.
AJOG Global Reports (2024) Vol. 4, Iss. 4, pp. 100386-100386
Open Access
Jonathan S. Schor, Adesh Kadambi, Isabel Fulcher, et al.
AJOG Global Reports (2024) Vol. 4, Iss. 4, pp. 100386-100386
Open Access
Machine learning for HELLP syndrome prediction: algorithms, case study and challenges
Keltoum Benlaharche, Hichem Bey Benlaharche
STUDIES IN ENGINEERING AND EXACT SCIENCES (2024) Vol. 5, Iss. 2, pp. e8237-e8237
Closed Access
Keltoum Benlaharche, Hichem Bey Benlaharche
STUDIES IN ENGINEERING AND EXACT SCIENCES (2024) Vol. 5, Iss. 2, pp. e8237-e8237
Closed Access
First‐Trimester Prediction Models Based on Maternal Characteristics for Adverse Pregnancy Outcomes: A Systematic Review and Meta‐Analysis
Jacintha C. A. van Eekhout, Ellis C. Becking, P Scheffer, et al.
BJOG An International Journal of Obstetrics & Gynaecology (2024)
Open Access
Jacintha C. A. van Eekhout, Ellis C. Becking, P Scheffer, et al.
BJOG An International Journal of Obstetrics & Gynaecology (2024)
Open Access