Prediction of severe preeclampsia in machine learning

Author:

Zhang Xinyuan,Chen YuORCID,Salerno Stephen,Li Yi,Zhou Libin,Zeng Xiaoxi,Li Huafeng

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Biomedical Engineering,Medicine (miscellaneous)

Reference36 articles.

1. Preeclampsia;Ramos;Rev Bras Ginecol Obstet,2017

2. Maternal obesity and severe pre-eclampsia among immigrant women: a mediation analysis;Siddiqui;Sci Rep,2020

3. Competing risks model in early screening for preeclampsia by biophysical and biochemical markers;Akolekar;Fetal Diagn Ther,2013

4. First-trimester screening for preeclampsia: impact of maternal parity on modeling and screening effectiveness;Moon;J Matern Fetal Neonatal Med,2014

5. Risk assessment for preeclampsia in nulliparous women at 11–13 weeks gestational age: prospective evaluation of two algorithms;Skråstad;BJOG,2014

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