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Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

dc.contributor.authorMalacova, Eva
dc.contributor.authorTippaya, Sawitchaya
dc.contributor.authorBailey, Helen D.
dc.contributor.authorChai, Kevin
dc.contributor.authorFarrant, Brad M.
dc.contributor.authorGebremedhin, Amanuel T.
dc.contributor.authorLeonard, Helen
dc.contributor.authorMarinovich, M. Luke
dc.contributor.authorNassar, Natasha
dc.contributor.authorPhatak, Aloke
dc.contributor.authorRaynes-Greenow, Camille
dc.contributor.authorRegan, Annette K.
dc.contributor.authorShand, Antonia W.
dc.contributor.authorShepherd, Carrington C. J.
dc.contributor.authorSrinivasjois, Ravisha
dc.contributor.authorTessema, Gizachew Assefa
dc.contributor.authorPereira, Gavin Francis
dc.date.accessioned2021-03-18T12:20:22Z
dc.date.available2021-03-18T12:20:22Z
dc.date.created2021-02-12T18:47:43Z
dc.date.issued2020
dc.identifier.citationScientific Reports. 2020, 10 .
dc.identifier.issn2045-2322
dc.identifier.urihttps://hdl.handle.net/11250/2734210
dc.language.isoeng
dc.titleStillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber8
dc.source.volume10
dc.source.journalScientific Reports
dc.identifier.doi10.1038/s41598-020-62210-9
dc.identifier.cristin1889394
dc.relation.projectNorges forskningsråd: 262700
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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