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.
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 .
A standardized knowledge sharing process has been implemented by using a semi-formal ontology for the representation of relevant clinical variables.
The development of DSSs, based on standardized knowledge, could be a tool to achieve a personalized decision-making.
Future oncology (London, England). 2017 Jul 31 [Epub ahead of print]
A R Alitto, R Gatta, Bgl Vanneste, M Vallati, E Meldolesi, A Damiani, V Lanzotti, G C Mattiucci, V Frascino, C Masciocchi, F Catucci, A Dekker, P Lambin, V Valentini, G Mantini
Radiation Oncology Area, Gemelli-ART, Catholic University of the Sacred Heart, Rome, Italy., Department of Radiation Oncology (MAASTRO), GROW - School for Oncology & Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands., School of Computing & Engineering, University of Huddersfield, Huddersfield, UK.
PubMed http://www.ncbi.nlm.nih.gov/pubmed/28758431
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PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE. - UroToday
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