Fuzzy expert system: An example in prostate cancer

Fuzzy set theory has been applied to many fields in which uncertainty is present as, for example, in medical diagnosis. In this paper, we propose a fuzzy expert system as an alternative to predict pathological stage of prostate cancer. Utilizing uncertain variables and approximate reasoning we construct a fuzzy rule-based system. Data of 190 patients submitted to radical prostatectomy were analyzed, seeking the test performance by the receiver operating characteristic (ROC) curve. The fuzzy expert system constructed is an additional tool to predict the pathological stage of prostate cancer and has a performance that is similar to the one presented by probability tables.