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Neurofuzzy Modeling to Determine Recurrence Risk Following Radical Cystectomy for Nonmetastatic Urothelial Carcinoma of the Bladder

This paper provides a design methodology for systems that can predict bladder cancer reoccurrence for patients who have undergone surgical operation to remove it. The system is based on neuro-fuzzy architecture that is trained using small data set. The prediction accuracy of the system is considerably high compared to other developed systems. The system also provides an average timing to reoccurrence, which helps on performing the appropriate monitoring procedure.