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PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE.
Alitto, A R; Gatta, R; Vanneste, Bgl; Vallati, M; Meldolesi, E; Damiani, A; Lanzotti, V; Mattiucci, G C; Frascino, V; Masciocchi, C; Catucci, F; Dekker, A; Lambin, P; Valentini, V; Mantini, G.
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  • Alitto AR; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Gatta R; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Vanneste B; Department of Radiation Oncology (MAASTRO), GROW - School for Oncology & Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
  • Vallati M; School of Computing & Engineering, University of Huddersfield, Huddersfield, UK.
  • Meldolesi E; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Damiani A; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Lanzotti V; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Mattiucci GC; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Frascino V; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Masciocchi C; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Catucci F; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Dekker A; Department of Radiation Oncology (MAASTRO), GROW - School for Oncology & Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
  • Lambin P; Department of Radiation Oncology (MAASTRO), GROW - School for Oncology & Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
  • Valentini V; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
  • Mantini G; Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy.
Future Oncol ; 13(24): 2171-2181, 2017 Oct.
Article en En | MEDLINE | ID: mdl-28758431
ABSTRACT

AIM:

Identifying the best care for a patient can be extremely challenging. To support the creation of multifactorial Decision Support Systems (DSSs), we propose an Umbrella Protocol, focusing on prostate cancer. MATERIALS &

METHODS:

The PRODIGE project consisted of a workflow for standardizing data, and procedures, to create a consistent dataset useful to elaborate DSSs. Techniques from classical statistics and machine learning will be adopted. The general protocol accepted by our Ethical Committee can be downloaded from cancerdata.org .

RESULTS:

A standardized knowledge sharing process has been implemented by using a semi-formal ontology for the representation of relevant clinical variables.

CONCLUSION:

The development of DSSs, based on standardized knowledge, could be a tool to achieve a personalized decision-making.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Próstata / Informática Médica / Programas Informáticos / Sistemas de Apoyo a Decisiones Clínicas / Medicina de Precisión Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Límite: Humans / Male Idioma: En Revista: Future Oncol 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: Neoplasias de la Próstata / Informática Médica / Programas Informáticos / Sistemas de Apoyo a Decisiones Clínicas / Medicina de Precisión Tipo de estudio: Guideline / Prognostic_studies / Risk_factors_studies Límite: Humans / Male Idioma: En Revista: Future Oncol Año: 2017 Tipo del documento: Article País de afiliación: Italia