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Machine learning prediction of hypertension and diabetes in twin pregnancies using characteristics at prenatal care entry: a nationwide study

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dc.contributor.coauthorMustafa HJ,
dc.contributor.coauthorPrasad S
dc.contributor.coauthorHeydari MH
dc.contributor.coauthorNunge RN
dc.contributor.coauthorKhalil A.
dc.contributor.departmentN/A
dc.contributor.kuauthorKalafat, Erkan
dc.contributor.schoolcollegeinstituteSchool of Medicine
dc.date.accessioned2024-12-29T09:40:08Z
dc.date.issued2024
dc.description.indexedbyPubMed
dc.description.publisherscopeInternational
dc.identifier.doi10.1002/uog.27710
dc.identifier.eissn1469-0705
dc.identifier.issn0960-7692
dc.identifier.quartileQ1
dc.identifier.urihttps://doi.org/10.1002/uog.27710
dc.identifier.urihttps://hdl.handle.net/20.500.14288/23215
dc.keywordsTwins
dc.keywordsArtificial intelligence
dc.keywordsCross‐sectional studies
dc.keywordsGestational diabetes
dc.keywordsGestational hypertension
dc.keywordsMachine learning
dc.keywordsPreeclampsia
dc.languageen
dc.publisherWiley
dc.sourceUltrasound in Obstetrics and Gynecology
dc.subjectObstetrics and gynecology
dc.titleMachine learning prediction of hypertension and diabetes in twin pregnancies using characteristics at prenatal care entry: a nationwide study
dc.typeJournal article
dspace.entity.typePublication
local.contributor.kuauthorKalafat, Erkan

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