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Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.

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Title: Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.
Authors: Nguyen-Hoang L; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR., Sahota DS; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR., Pooh RK; CRIFM Prenatal Medical Clinic, Osaka, Japan., Duan H; Nanjing Drum Tower Hospital, Nanjing, China., Chaiyasit N; King Chulalongkorn Memorial Hospital, Bangkok, Thailand., Sekizawa A; Showa University Hospital, Tokyo, Japan., Shaw SW; Taipei Chang Gung Memorial Hospital, Taipei, Taiwan., Seshadri S; Mediscan, Chennai, India., Choolani M; National University Hospital, Singapore., Yapan P; Faculty of Medicine, Siriraj Hospital, Bangkok, Thailand., Sim WS; Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore., Ma R; First Affiliated Hospital of Kunming Medical University, Kunming, China., Leung WC; Kwong Wah Hospital, Hong Kong SAR., Lau SL; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR., Lee NMW; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR., Leung HYH; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR., Meshali T; Department of Mathematics, Bar Ilan University, Ramat Gan, Israel., Meiri H; The ASPRE Consortium and TeleMarpe, Tel Aviv, Israel., Louzoun Y; Department of Mathematics, Bar Ilan University, Ramat Gan, Israel., Poon LC; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.
Source: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics [Int J Gynaecol Obstet] 2024 Oct; Vol. 167 (1), pp. 350-359. Date of Electronic Publication: 2024 Apr 26.
Publication Type: Journal Article; Multicenter Study; Validation Study
Journal Info: Publisher: Wiley Country of Publication: United States NLM ID: 0210174 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-3479 (Electronic) Linking ISSN: 00207292 NLM ISO Abbreviation: Int J Gynaecol Obstet Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.
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  Data: <searchLink fieldCode="AU" term="%22Nguyen-Hoang+L%22">Nguyen-Hoang L</searchLink>; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.<br /><searchLink fieldCode="AU" term="%22Sahota+DS%22">Sahota DS</searchLink>; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.<br /><searchLink fieldCode="AU" term="%22Pooh+RK%22">Pooh RK</searchLink>; CRIFM Prenatal Medical Clinic, Osaka, Japan.<br /><searchLink fieldCode="AU" term="%22Duan+H%22">Duan H</searchLink>; Nanjing Drum Tower Hospital, Nanjing, China.<br /><searchLink fieldCode="AU" term="%22Chaiyasit+N%22">Chaiyasit N</searchLink>; King Chulalongkorn Memorial Hospital, Bangkok, Thailand.<br /><searchLink fieldCode="AU" term="%22Sekizawa+A%22">Sekizawa A</searchLink>; Showa University Hospital, Tokyo, Japan.<br /><searchLink fieldCode="AU" term="%22Shaw+SW%22">Shaw SW</searchLink>; Taipei Chang Gung Memorial Hospital, Taipei, Taiwan.<br /><searchLink fieldCode="AU" term="%22Seshadri+S%22">Seshadri S</searchLink>; Mediscan, Chennai, India.<br /><searchLink fieldCode="AU" term="%22Choolani+M%22">Choolani M</searchLink>; National University Hospital, Singapore.<br /><searchLink fieldCode="AU" term="%22Yapan+P%22">Yapan P</searchLink>; Faculty of Medicine, Siriraj Hospital, Bangkok, Thailand.<br /><searchLink fieldCode="AU" term="%22Sim+WS%22">Sim WS</searchLink>; Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore.<br /><searchLink fieldCode="AU" term="%22Ma+R%22">Ma R</searchLink>; First Affiliated Hospital of Kunming Medical University, Kunming, China.<br /><searchLink fieldCode="AU" term="%22Leung+WC%22">Leung WC</searchLink>; Kwong Wah Hospital, Hong Kong SAR.<br /><searchLink fieldCode="AU" term="%22Lau+SL%22">Lau SL</searchLink>; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.<br /><searchLink fieldCode="AU" term="%22Lee+NMW%22">Lee NMW</searchLink>; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.<br /><searchLink fieldCode="AU" term="%22Leung+HYH%22">Leung HYH</searchLink>; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.<br /><searchLink fieldCode="AU" term="%22Meshali+T%22">Meshali T</searchLink>; Department of Mathematics, Bar Ilan University, Ramat Gan, Israel.<br /><searchLink fieldCode="AU" term="%22Meiri+H%22">Meiri H</searchLink>; The ASPRE Consortium and TeleMarpe, Tel Aviv, Israel.<br /><searchLink fieldCode="AU" term="%22Louzoun+Y%22">Louzoun Y</searchLink>; Department of Mathematics, Bar Ilan University, Ramat Gan, Israel.<br /><searchLink fieldCode="AU" term="%22Poon+LC%22">Poon LC</searchLink>; Department of Obstetrics and Gynecology, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong SAR.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley%22">Wiley </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0210174 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1879-3479 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200207292%22">00207292 </searchLink><i>NLM ISO Abbreviation: </i>Int J Gynaecol Obstet <i>Subsets: </i>MEDLINE
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        Value: 10.1002/ijgo.15563
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        Text: English
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              Text: 2024 Oct
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