Fuzzy expert system for predicting pathological stage of prostate cancer

被引：39

作者：

Castanho, M. J. P. ^{[1
]}

Hernandes, F. ^{[2
]}

De Re, A. M. ^{[2
]}

Rautenberg, S. ^{[2
]}

Billis, A. ^{[3
]}

机构：

[1] Univ Estadual Centro Oeste, Dept Math, Guarapuava, PR, Brazil

[2] Univ Estadual Centro Oeste, Dept Computat Sci, Guarapuava, PR, Brazil

[3] Univ Estadual Campinas, Sch Med, Campinas, SP, Brazil

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2013年 / 40卷 / 02期

关键词：

Fuzzy rule-based system; Genetic algorithm; Prostate cancer; ARTIFICIAL NEURAL-NETWORKS; PARTIN TABLES; CLINICAL STAGE; GLEASON SCORE; NOMOGRAMS; BREAST; CATALOG; ANTIGEN;

D O I：

10.1016/j.eswa.2012.07.046

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：466 / 470

页数：5

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