Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms.
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| Title: | Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms. |
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| Authors: | Kang BS; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Lee SU; Department of Obstetrics and Gynecology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Hong S; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Choi SK; Department of Obstetrics and Gynecology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Shin JE; Department of Obstetrics and Gynecology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Wie JH; Department of Obstetrics and Gynecology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Jo YS; Department of Obstetrics and Gynecology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Kim YH; Department of Obstetrics and Gynecology, Uijeongbu St. Mary's Hospital,, College of Medicine, The Catholic University of Korea, Seoul, Korea., Kil K; Department of Obstetrics and Gynecology, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Chung YH; Department of Obstetrics and Gynecology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Jung K; Innerwave Co., Ltd, Seoul, Korea., Hong H; Innerwave Co., Ltd, Seoul, Korea., Park IY; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea., Ko HS; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea. mongkoko@catholic.ac.kr. |
| Source: | Scientific reports [Sci Rep] 2023 Aug 16; Vol. 13 (1), pp. 13356. Date of Electronic Publication: 2023 Aug 16. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 37587201 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Kang+BS%22">Kang BS</searchLink>; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Lee+SU%22">Lee SU</searchLink>; Department of Obstetrics and Gynecology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Hong+S%22">Hong S</searchLink>; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Choi+SK%22">Choi SK</searchLink>; Department of Obstetrics and Gynecology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Shin+JE%22">Shin JE</searchLink>; Department of Obstetrics and Gynecology, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Wie+JH%22">Wie JH</searchLink>; Department of Obstetrics and Gynecology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Jo+YS%22">Jo YS</searchLink>; Department of Obstetrics and Gynecology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Kim+YH%22">Kim YH</searchLink>; Department of Obstetrics and Gynecology, Uijeongbu St. Mary's Hospital,, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Kil+K%22">Kil K</searchLink>; Department of Obstetrics and Gynecology, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Chung+YH%22">Chung YH</searchLink>; Department of Obstetrics and Gynecology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Jung+K%22">Jung K</searchLink>; Innerwave Co., Ltd, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Hong+H%22">Hong H</searchLink>; Innerwave Co., Ltd, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Park+IY%22">Park IY</searchLink>; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.<br /><searchLink fieldCode="AU" term="%22Ko+HS%22">Ko HS</searchLink>; Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea. mongkoko@catholic.ac.kr. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2023 Aug 16; Vol. 13 (1), pp. 13356. <i>Date of Electronic Publication: </i>2023 Aug 16. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article; Research Support, Non-U.S. Gov't – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101563288 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2045-2322 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2220452322%22">20452322 </searchLink><i>NLM ISO Abbreviation: </i>Sci Rep <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=37587201 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41598-023-39680-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 13356 Titles: – TitleFull: Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kang BS – PersonEntity: Name: NameFull: Lee SU – PersonEntity: Name: NameFull: Hong S – PersonEntity: Name: NameFull: Choi SK – PersonEntity: Name: NameFull: Shin JE – PersonEntity: Name: NameFull: Wie JH – PersonEntity: Name: NameFull: Jo YS – PersonEntity: Name: NameFull: Kim YH – PersonEntity: Name: NameFull: Kil K – PersonEntity: Name: NameFull: Chung YH – PersonEntity: Name: NameFull: Jung K – PersonEntity: Name: NameFull: Hong H – PersonEntity: Name: NameFull: Park IY – PersonEntity: Name: NameFull: Ko HS IsPartOfRelationships: – BibEntity: Dates: – D: 16 M: 08 Text: 2023 Aug 16 Type: published Y: 2023 Identifiers: – Type: issn-electronic Value: 2045-2322 Numbering: – Type: volume Value: 13 – Type: issue Value: 1 Titles: – TitleFull: Scientific reports Type: main |
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