A Fuzzy Expert System Design for Diagnosis of Prostate Cancer

Artificial Intelligence in computer science has interested many computer scientists in recent era. In recent years, Artificial Intelligence has been used widely in the field of medical hence numerous numbers of expert systems have been developed for diagnosing and treating different diseases especially cancer. But, somehow many of the cancer expert systems are unable to assists the doctors and urologists. Prostate Cancer is the most well-known sort of cancer that evolves in male. In recent times, prostate cancer has been evolved epidemically. To deal with this problem, proposed a Fuzzy Expert Prostate Cancer System (FEPCS) that diagnose and the stage of prostate cancer. To deal with the input parameters like Prostate Specific Antigen (PSA), Gleason Score, Metastasis, Age, Ethnicity etc. a set of fuzzy rules and expert opinion have used to calculate the risk of prostate cancer (PCR). FEPCS designed using MATLAB. In this research, 225 patient records have used and the accuracy of FEPCS is 81 percent according to confusion matrix.