Prediction Model of Late Fetal Growth Restriction with Machine Learning Algorithms

Background: This study aimed to develop a clinical model to predict late-onset fetal growth restriction (FGR). Methods: This retrospective study included seven hospitals and was conducted between January 2009 and December 2020. Two sets of variables from the first trimester until 13 weeks (E1) and t...

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Bibliografiske detaljer

Principais autores:	Seon Ui Lee, Sae Kyung Choi, Yun Sung Jo, Jeong Ha Wie, Jae Eun Shin, Yeon Hee Kim, Kicheol Kil, Hyun Sun Ko
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2024-11-01
Serier:	Life
Fag:	fetal growth restriction gestation machine learning
Online adgang:	https://www.mdpi.com/2075-1729/14/11/1521
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