کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
383200 | 660808 | 2013 | 5 صفحه PDF | دانلود رایگان |

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.
► We model a system for predicting pathological stage of prostate cancer.
► We develop a hybrid system: a rule-based fuzzy system where a genetic algorithm is used to optimize the parameters.
► Performance of genetic-fuzzy system constructed, for the database used, show superior Partin tables.
Journal: Expert Systems with Applications - Volume 40, Issue 2, 1 February 2013, Pages 466–470