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• W2000697678 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." @default.
• W2000697678 created "2016-06-24" @default.
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• W2000697678 date "2013-02-01" @default.
• W2000697678 modified "2023-10-02" @default.
• W2000697678 title "Fuzzy expert system for predicting pathological stage of prostate cancer" @default.
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• W2000697678 doi "https://doi.org/10.1016/j.eswa.2012.07.046" @default.
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