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.

Alitto, A., Gatta, R., Vanneste, B., Vallati, M., Meldolesi, E., Damiani, A., Lanzotti, V., Mattiucci, G., Frascino, V., Masciocchi, C., Catucci, F., Dekker, A., Lambin, P., Valentini, V., Mantini, G., PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE, <<FUTURE ONCOLOGY>>, 2017; 13 (24): 2171-2181. [doi:10.2217/fon-2017-0142] [http://hdl.handle.net/10807/149298]

PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE

Alitto, A.;Meldolesi, E.;Damiani, A.;Mattiucci, G.;Frascino, V.;Masciocchi, C.;Valentini, V.;Mantini, G.
2017

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.
Inglese
Alitto, A., Gatta, R., Vanneste, B., Vallati, M., Meldolesi, E., Damiani, A., Lanzotti, V., Mattiucci, G., Frascino, V., Masciocchi, C., Catucci, F., Dekker, A., Lambin, P., Valentini, V., Mantini, G., PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE, <<FUTURE ONCOLOGY>>, 2017; 13 (24): 2171-2181. [doi:10.2217/fon-2017-0142] [http://hdl.handle.net/10807/149298]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/149298
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