Identifying the Early Signs of Preterm Birth from U.S. Birth Records Using Machine Learning Techniques

Preterm birth (PTB) is the leading cause of infant mortality in the U.S. and globally. The goal of this study is to increase understanding of PTB risk factors that are present early in pregnancy by leveraging statistical and machine learning (ML) techniques on big data. The 2016 U.S. birth records w...

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Bibliographic Details
Main Authors:	Ebrahimvandi, A. (Author), Hosseinichimeh, N. (Author), Kong, Z.J (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Adaptive boosting Decision trees education Gradient boosting Infant mortality Logistic regression Machine learning Machine learning techniques neural networks Neural-networks Predictive power Preterm birth racial disparities Racial disparity Random forests Risk factors Socio-economic factor socioeconomic factors statistical analysis Statistical learning techniques
Online Access:	View Fulltext in Publisher

Internet

View Fulltext in Publisher

Identifying the Early Signs of Preterm Birth from U.S. Birth Records Using Machine Learning Techniques

Internet

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