PRODIGE: Prediction Models in Prostate Cancer for Personalized Medicine Challenge
A.R. Alitto, Roberto Gatta, B. Vanneste, Mauro Vallati, Elisa Meldolesi, Andrea Damiani, Vito Lanzotti, Gian Carlo Mattiucci, V. Frascino, Carlotta Masciocchi, Francesco Catucci, Andre L.A.J. Dekker, Philippe Lambin, Vincenzo Valentini, Giovanna Mantini · Future Oncology · 2017
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.