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Machine-learning prediction model for gestational diabetes in twin pregnancies: population-based cohort study

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dc.contributor.coauthorMustafa, Hiba
dc.contributor.coauthorHeydari, Mohammad-Hossein
dc.contributor.coauthorNunge, Rebecca
dc.contributor.coauthorKhalil, Asma
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorKalafat, Erkan
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2024-12-29T09:36:38Z
dc.date.issued2023
dc.description.abstractTo develop a prediction model for hypertensive disorders in pregnancy (HDP) and gestational diabetes (GDM) in twin pregnancies utilizing characteristics at the prenatal care entry level.
dc.description.indexedbyWOS
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume130
dc.identifier.eissn1471-0528
dc.identifier.issn1470-0328
dc.identifier.quartileQ1
dc.identifier.urihttps://hdl.handle.net/20.500.14288/22103
dc.identifier.wos1050510600070
dc.keywordsObstetrics
dc.keywordsGynecology
dc.language.isoeng
dc.publisherWiley
dc.relation.ispartofBJOG-An International Journal of Obstetrics and Gynaecology
dc.subjectMedicine
dc.titleMachine-learning prediction model for gestational diabetes in twin pregnancies: population-based cohort study
dc.typeMeeting Abstract
dc.type.otherMeeting abstract
dspace.entity.typePublication
local.contributor.kuauthorKalafat, Erkan
local.publication.orgunit1SCHOOL OF MEDICINE
local.publication.orgunit2School of Medicine
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relation.isOrgUnitOfPublication.latestForDiscoveryd02929e1-2a70-44f0-ae17-7819f587bedd
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relation.isParentOrgUnitOfPublication.latestForDiscovery17f2dc8e-6e54-4fa8-b5e0-d6415123a93e

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