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

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

Internet

http://purl.org/au-research/grants/nhmrc/1099655
http://hdl.handle.net/20.500.11937/93230

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