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Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters.
Esteban-Escaño, Javier; Castán, Berta; Castán, Sergio; Chóliz-Ezquerro, Marta; Asensio, César; Laliena, Antonio R; Sanz-Enguita, Gerardo; Sanz, Gerardo; Esteban, Luis Mariano; Savirón, Ricardo.
Afiliação
  • Esteban-Escaño J; Department of Electronic Engineering and Communications, Escuela Universitaria Politécnica de La Almunia, Universidad de Zaragoza, Calle Mayor 5, 50100 La Almunia de Doña Godina, Spain.
  • Castán B; Department of Obstetrics and Gynecology, San Pedro Hospital, Calle Piqueras 98, 26006 Logroño, Spain.
  • Castán S; Department of Obstetrics and Gynecology, Miguel Servet University Hospital, Paseo Isabel La Católica 3, 50009 Zaragoza, Spain.
  • Chóliz-Ezquerro M; Department of Obstetrics, Dexeus University Hospital, Gran Via de Carles III 71-75, 08028 Barcelona, Spain.
  • Asensio C; Department of Applied Mathematics, Escuela Universitaria Politécnica de La Almunia, Universidad de Zaragoza, Calle Mayor 5, 50100 La Almunia de Doña Godina, Spain.
  • Laliena AR; Department of Applied Mathematics, Escuela Universitaria Politécnica de La Almunia, Universidad de Zaragoza, Calle Mayor 5, 50100 La Almunia de Doña Godina, Spain.
  • Sanz-Enguita G; Department of Applied Physics, Escuela Universitaria Politécnica de La Almunia, Universidad de Zaragoza, Calle Mayor 5, 50100 La Almunia de Doña Godina, Spain.
  • Sanz G; Department of Statistical Methods and Institute for Biocomputation and Physics of Complex Systems-BIFI, University of Zaragoza, Calle Pedro Cerbuna 12, 50009 Zaragoza, Spain.
  • Esteban LM; Department of Applied Mathematics, Escuela Universitaria Politécnica de La Almunia, Universidad de Zaragoza, Calle Mayor 5, 50100 La Almunia de Doña Godina, Spain.
  • Savirón R; Department of Obstetrics and Gynecology, Hospital Clínico San Carlos and Instituto de Investigación Sanitaria San Carlos (IdISSC), Universidad Complutense, Calle del Prof Martín Lagos s/n, 28040 Madrid, Spain.
Entropy (Basel) ; 24(1)2021 Dec 30.
Article em En | MEDLINE | ID: mdl-35052094
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha