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  1. Pubblicazioni

PRODIGE: PRediction models in prOstate cancer for personalized meDIcine challenGE

Articolo
Data di Pubblicazione:
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.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Decision Support System; individualized medicine; large database; machine learning; ontology; predictive model; Humans; Machine Learning; Male; Medical Informatics; Prognosis; Prostatic Neoplasms; Workflow; Decision Support Systems, Clinical; Precision Medicine; Software
Elenco autori:
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.
Autori di Ateneo:
GATTA ROBERTO
Link alla scheda completa:
https://iris.unibs.it/handle/11379/546279
Pubblicato in:
FUTURE ONCOLOGY
Journal
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