A New XGBoost Algorithm Based Prediction Model for Fetal Growth Restriction in Patients with Preeclampsia

A New XGBoost Algorithm Based Prediction Model for Fetal Growth Restriction in Patients with Preeclampsia

Background: To construct a predictive model for fetal growth restriction (FGR) in preeclampsia (PE) patients using extreme Gradient Boosting (XGBoost) algorithm. Methods: A prospective study was conducted in the Obstetrics Department of Wuming Hospital from October 1, 2016, to October 1, 2021. A tot...

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Bibliographic Details
Main Authors: Haijuan Li, Sumei Wang, Chunyu Zhan
Format: Article
Language:English
Published: IMR Press 2023-08-01
Series:Clinical and Experimental Obstetrics & Gynecology
Subjects:
fetal growth restriction
machine learning
multivariate analysis
preeclampsia
risk factors
xgboost algorithm
Online Access:https://www.imrpress.com/journal/CEOG/50/8/10.31083/j.ceog5008172

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https://www.imrpress.com/journal/CEOG/50/8/10.31083/j.ceog5008172

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