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Addressing practical issues of predictive models translation into everyday practice and public health management: a combined model to predict the risk of type 2 diabetes improves incidence prediction and reduces the prevalence of missing risk predictions.
Vettoretti, Martina; Longato, Enrico; Zandonà, Alessandro; Li, Yan; Pagán, José Antonio; Siscovick, David; Carnethon, Mercedes R; Bertoni, Alain G; Facchinetti, Andrea; Di Camillo, Barbara.
Afiliación
  • Vettoretti M; Department of Information Engineering, School of Engineering, University of Padova, Padova, Italy.
  • Longato E; Department of Information Engineering, School of Engineering, University of Padova, Padova, Italy.
  • Zandonà A; Department of Information Engineering, School of Engineering, University of Padova, Padova, Italy.
  • Li Y; Icahn School of Medicine at Mount Sinai, New York, New York, USA.
  • Pagán JA; Department of Public Health Policy and Management, New York University, New York, New York, USA.
  • Siscovick D; Center for Health Innovation, New York Academy of Medicine, New York, New York, USA.
  • Carnethon MR; Research, Evaluation & Policy, New York Academy of Medicine, New York, New York, USA.
  • Bertoni AG; Department of Preventive Medicine, Northwestern University, Chicago, Illinois, USA.
  • Facchinetti A; Division of Public Health Sciences, Wake Forest University Health Sciences, Winston-Salem, North Carolina, USA.
  • Di Camillo B; Department of Information Engineering, School of Engineering, University of Padova, Padova, Italy.
BMJ Open Diabetes Res Care ; 8(1)2020 07.
Article en En | MEDLINE | ID: mdl-32747386
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diabetes Mellitus Tipo 2 Tipo de estudio: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: BMJ Open Diabetes Res Care Año: 2020 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: Diabetes Mellitus Tipo 2 Tipo de estudio: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: BMJ Open Diabetes Res Care Año: 2020 Tipo del documento: Article País de afiliación: Italia