PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE

Anna Rita Alitto, Roberto Gatta, Bgl Vanneste, M. Vallati, Elisa Meldolesi, Andrea Damiani, V. Lanzotti, Gian Carlo Mattiucci, Vincenzo Frascino, Carlotta Masciocchi, Francesco Catucci, A. Dekker, Alain Dekker, P. Lambin, Vincenzo Valentini, Giovanna Mantini

Risultato della ricerca: Contributo in rivistaArticolo in rivista

7 Citazioni (Scopus)


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 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.
Lingua originaleEnglish
pagine (da-a)2171-2181
Numero di pagine11
RivistaFuture Oncology
Stato di pubblicazionePubblicato - 2017


  • Cancer Research
  • Decision Support System
  • Oncology
  • individualized medicine
  • large database
  • machine learning
  • ontology
  • predictive model


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