View in EDS HTML Full Text PDF Full Text

New advances in prediction and surveillance of preeclampsia: role of machine learning approaches and remote monitoring.

Saved in:
Bibliographic Details
Title: New advances in prediction and surveillance of preeclampsia: role of machine learning approaches and remote monitoring.
Authors: Hackelöer M; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany., Schmidt L; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany., Verlohren S; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany. stefan.verlohren@charite.de.
Source: Archives of gynecology and obstetrics [Arch Gynecol Obstet] 2023 Dec; Vol. 308 (6), pp. 1663-1677. Date of Electronic Publication: 2022 Dec 25.
Publication Type: Journal Article; Review
Journal Info: Publisher: Springer Verlag Country of Publication: Germany NLM ID: 8710213 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-0711 (Electronic) Linking ISSN: 09320067 NLM ISO Abbreviation: Arch Gynecol Obstet Subsets: MEDLINE
Database: MEDLINE Ultimate
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 36566477
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: New advances in prediction and surveillance of preeclampsia: role of machine learning approaches and remote monitoring.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Hackelöer+M%22">Hackelöer M</searchLink>; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.<br /><searchLink fieldCode="AU" term="%22Schmidt+L%22">Schmidt L</searchLink>; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.<br /><searchLink fieldCode="AU" term="%22Verlohren+S%22">Verlohren S</searchLink>; Department of Obstetrics, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany. stefan.verlohren@charite.de.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%228710213%22">Archives of gynecology and obstetrics</searchLink> [Arch Gynecol Obstet] 2023 Dec; Vol. 308 (6), pp. 1663-1677. <i>Date of Electronic Publication: </i>2022 Dec 25.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article; Review
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+Verlag%22">Springer Verlag </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>8710213 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1432-0711 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209320067%22">09320067 </searchLink><i>NLM ISO Abbreviation: </i>Arch Gynecol Obstet <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=36566477
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00404-022-06864-y
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 1663
    Titles:
      – TitleFull: New advances in prediction and surveillance of preeclampsia: role of machine learning approaches and remote monitoring.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hackelöer M
      – PersonEntity:
          Name:
            NameFull: Schmidt L
      – PersonEntity:
          Name:
            NameFull: Verlohren S
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: 2023 Dec
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-electronic
              Value: 1432-0711
          Numbering:
            – Type: volume
              Value: 308
            – Type: issue
              Value: 6
          Titles:
            – TitleFull: Archives of gynecology and obstetrics
              Type: main
ResultId 1