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RERT: A Novel Regression Tree Approach to Predict Extrauterine Disease in Endometrial Carcinoma Patients.
Vezzoli, Marika; Ravaggi, Antonella; Zanotti, Laura; Miscioscia, Rebecca Angelica; Bignotti, Eliana; Ragnoli, Monica; Gambino, Angela; Ruggeri, Giuseppina; Calza, Stefano; Sartori, Enrico; Odicino, Franco.
Afiliación
  • Vezzoli M; Department of Molecular and Translational Medicine, Unit of Biostatistics, University of Brescia, Brescia, Italy. marika.vezzoli@unibs.it.
  • Ravaggi A; "Angelo Nocivelli" Institute of Molecular Medicine, Division of Obstetrics and Gynecology, University of Brescia, Brescia, Italy. antonella.ravaggi@unibs.it.
  • Zanotti L; "Angelo Nocivelli" Institute of Molecular Medicine, Division of Obstetrics and Gynecology, University of Brescia, Brescia, Italy.
  • Miscioscia RA; Department of Obstetrics and Gynecology, University of Brescia, Brescia, Italy.
  • Bignotti E; Division of Obstetrics and Gynecology, ASST Spedali Civili of Brescia, Brescia, Italy.
  • Ragnoli M; Division of Obstetrics and Gynecology, ASST Spedali Civili of Brescia, Brescia, Italy.
  • Gambino A; Department of Obstetrics and Gynecology, University of Brescia, Brescia, Italy.
  • Ruggeri G; Laboratory Analysis, ASST Spedali Civili of Brescia, Brescia, Italy.
  • Calza S; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Sartori E; Department of Obstetrics and Gynecology, University of Brescia, Brescia, Italy.
  • Odicino F; Department of Obstetrics and Gynecology, University of Brescia, Brescia, Italy.
Sci Rep ; 7(1): 10528, 2017 09 05.
Article en En | MEDLINE | ID: mdl-28874808
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Carcinoma / Neoplasias Endometriales Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Middle aged Idioma: En Revista: Sci Rep Año: 2017 Tipo del documento: Article País de afiliación: Italia
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Carcinoma / Neoplasias Endometriales Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Middle aged Idioma: En Revista: Sci Rep Año: 2017 Tipo del documento: Article País de afiliación: Italia