Fuzzy expert system for predicting pathological stage of prostate cancer

Authors:
M. J. P. Castanho;F. Hernandes;A. M. De Ré;S. Rautenberg;A. Billis
Affiliations:
Department of Mathematics, Universidade Estadual do Centro-Oeste, Guarapuava, PR, Brazil;Department of Computation Science, Universidade Estadual do Centro-Oeste, Guarapuava, PR, Brazil;Department of Computation Science, Universidade Estadual do Centro-Oeste, Guarapuava, PR, Brazil;Department of Computation Science, Universidade Estadual do Centro-Oeste, Guarapuava, PR, Brazil;School of Medicine, Universidade Estadual de Campinas, Campinas, SP, Brazil
Venue:
Expert Systems with Applications: An International Journal
Year:
2013

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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.