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|Type:||Artigo de periódico|
|Title:||Fuzzy expert system for predicting pathological stage of prostate cancer|
De Re, AM
|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|
|Editor:||Pergamon-elsevier Science Ltd|
|Citation:||Expert Systems With Applications. Pergamon-elsevier Science Ltd, v. 40, n. 2, n. 466, n. 470, 2013.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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