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Machine learning models for predicting preeclampsia: a systematic review

Machine learning models for predicting preeclampsia: a systematic review

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_ec4da3c13f9244a6ba3a21c79c7199e2

Machine learning models for predicting preeclampsia: a systematic review

About this item

Full title

Machine learning models for predicting preeclampsia: a systematic review

Publisher

England: BioMed Central Ltd

Journal title

BMC Pregnancy and Childbirth, 2024-01, Vol.24 (1), p.6-6, Article 6

Language

English

Formats

Publication information

Publisher

England: BioMed Central Ltd

More information

Scope and Contents

Contents

This systematic review provides an overview of machine learning (ML) approaches for predicting preeclampsia.
This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) guidelines. We searched the Cochrane Central Register, PubMed, EMBASE, ProQuest, Scopus, and Google Scholar up to February 2023. Search...

Alternative Titles

Full title

Machine learning models for predicting preeclampsia: a systematic review

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_ec4da3c13f9244a6ba3a21c79c7199e2

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_ec4da3c13f9244a6ba3a21c79c7199e2

Other Identifiers

ISSN

1471-2393

E-ISSN

1471-2393

DOI

10.1186/s12884-023-06220-1

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