Prediction model development of late-onset preeclampsia using machine learning-based methods-Reference-Cited by-同舟云学术

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Prediction model development of late-onset preeclampsia using machine learning-based methods

Published:2019-08-23 Issue:8 Volume:14 Page:e0221202
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Jhee Jong Hyun,Lee SungHee,Park Yejin,Lee Sang Eun,Kim Young Ah,Kang Shin-Wook,Kwon Ja-Young,Park Jung Tak

Funder

Ministry of Trade, Industry and Energy Grant funded by the Korean government

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference47 articles.

1. Pre-eclampsia;BWJ Mol;Lancet,2016

2. Pre-eclampsia rates in the United States, 1980–2010: age-period-cohort analysis;CV Ananth;Bmj,2013

3. A prospective study of maternal, fetal and neonatal deaths in low- and middle-income countries;S Saleem;Bull World Health Organ,2014

4. Long-term maternal and subsequent pregnancy outcomes 5 years after hemolysis, elevated liver enzymes, and low platelets (HELLP) syndrome;M Habli;Am J Obstet Gynecol.,2009

5. Placental pathology suggesting that preeclampsia is more than one disease;DB Nelson;Am J Obstet Gynecol,2014

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