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Type: Artigo de periódico
Title: Fuzzy expert system for predicting pathological stage of prostate cancer
Author: Castanho, MJP
Hernandes, F
De Re, AM
Rautenberg, S
Billis, A
Abstract: Prostate cancer is the second most common cancer among men, responsible for the loss of half a million lives each year worldwide, according to the World Health Organization. In prostate cancer, definitive therapy such as radical prostatectomy, is more effective when the cancer is organ-confined. The aim of this study is to investigate the performance of some fuzzy expert systems in the classification of patients with confined or non-confined cancer. To deal with the intrinsic uncertainty about the variables utilized to predict cancer stage, the developed approach is based on Fuzzy Set Theory. A fuzzy expert system was developed with the fuzzy rules and membership functions tuned by a genetic algorithm. As a result, the utilized approach reached better precision taking into account some correlated studies. (C) 2012 Elsevier Ltd. All rights reserved.
Subject: Fuzzy rule-based system
Genetic algorithm
Prostate cancer
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Citation: Expert Systems With Applications. Pergamon-elsevier Science Ltd, v. 40, n. 2, n. 466, n. 470, 2013.
Rights: fechado
Identifier DOI: 10.1016/j.eswa.2012.07.046
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

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