Development of prognostic model for preterm birth using machine learning in a population-based cohort of Western Australia births between 1980 and 2015

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Development of prognostic model for preterm birth using machine learning in a population-based cohort of Western Australia births between 1980 and 2015

Preterm birth is a global public health problem with a significant burden on the individuals affected. The study aimed to extend current research on preterm birth prognostic model development by developing and internally validating models using machine learning classification algorithms and populati...

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Bibliographic Details
Main Authors:	Wong, Kingsley, Tessema, Gizachew, Chai, Kevin, Pereira, Gavin
Format:	Journal Article
Language:	English
Published:	NATURE PORTFOLIO 2022
Subjects:	Science & Technology Multidisciplinary Sciences Science & Technology - Other Topics HIGH-RISK OUTCOMES Pregnancy Infant, Newborn Humans Female Premature Birth Western Australia Retrospective Studies Prognosis Risk Factors Cohort Studies Machine Learning
Online Access:	http://purl.org/au-research/grants/nhmrc/1099655 http://hdl.handle.net/20.500.11937/93230

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