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Artificial intelligence and machine learning in cardiotocography: A scoping review.
Aeberhard, Jasmin L; Radan, Anda-Petronela; Delgado-Gonzalo, Ricard; Strahm, Karin Maya; Sigurthorsdottir, Halla Bjorg; Schneider, Sophie; Surbek, Daniel.
Afiliación
  • Aeberhard JL; Medical Faculty of the University of Bern, Switzerland. Electronic address: jasmin-aeberhard@bluewin.ch.
  • Radan AP; Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
  • Delgado-Gonzalo R; Centre Suisse d'Électronique et de Microtechnique CSEM, Neuchâtel, Switzerland.
  • Strahm KM; Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
  • Sigurthorsdottir HB; Centre Suisse d'Électronique et de Microtechnique CSEM, Neuchâtel, Switzerland.
  • Schneider S; Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
  • Surbek D; Department of Obstetrics and Feto-maternal Medicine, University Hospital of Bern, Switzerland.
Eur J Obstet Gynecol Reprod Biol ; 281: 54-62, 2023 Feb.
Article en En | MEDLINE | ID: mdl-36535071
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Cardiotocografía Tipo de estudio: Guideline / Prognostic_studies / Systematic_reviews Límite: Female / Humans / Pregnancy Idioma: En Revista: Eur J Obstet Gynecol Reprod Biol Año: 2023 Tipo del documento: Article
Texto completo
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Cardiotocografía Tipo de estudio: Guideline / Prognostic_studies / Systematic_reviews Límite: Female / Humans / Pregnancy Idioma: En Revista: Eur J Obstet Gynecol Reprod Biol Año: 2023 Tipo del documento: Article