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Machine learning application for development of a data-driven predictive model able to investigate quality of life scores in a rare disease.
Spiga, Ottavia; Cicaloni, Vittoria; Fiorini, Cosimo; Trezza, Alfonso; Visibelli, Anna; Millucci, Lia; Bernardini, Giulia; Bernini, Andrea; Marzocchi, Barbara; Braconi, Daniela; Prischi, Filippo; Santucci, Annalisa.
Afiliação
  • Spiga O; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy. ottavia.spiga@unisi.it.
  • Cicaloni V; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Fiorini C; Toscana Life Sciences Foundation, Siena, Italy.
  • Trezza A; Energy way, Modena, Italy.
  • Visibelli A; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Millucci L; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Bernardini G; Department of Information Engineering and Mathematics, University of Siena, Siena, Italy.
  • Bernini A; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Marzocchi B; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Braconi D; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Prischi F; Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Via A., 53100, Siena, Italy.
  • Santucci A; UOC Patologia Clinica, Azienda Ospedaliera Senese, Siena, Italy.
Orphanet J Rare Dis ; 15(1): 46, 2020 02 12.
Article em En | MEDLINE | ID: mdl-32050984
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Alcaptonúria Idioma: En Ano de publicação: 2020 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Qualidade de Vida / Alcaptonúria Idioma: En Ano de publicação: 2020 Tipo de documento: Article