Comparison of logistic regression with machine learning methods for the prediction of fetal growth abnormalities: a retrospective cohort study

Abstract Background While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objective of the current study was to identify pr...

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Detalhes bibliográficos

Principais autores:	Stefan Kuhle, Bryan Maguire, Hongqun Zhang, David Hamilton, Alexander C. Allen, K. S. Joseph, Victoria M. Allen
Formato:	Artigo
Idioma:	Inglês
Publicado em:	BMC 2018-08-01
coleção:	BMC Pregnancy and Childbirth
Assuntos:	Pregnancy Infant Prediction Birth weight Fetal growth restriction Fetal macrosomia
Acesso em linha:	http://link.springer.com/article/10.1186/s12884-018-1971-2
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