Implementation of Fuzzy-based Model for Prediction of Prostate Cancer

Abstract

Abstract Cancer is one of the leading causes of death worldwide. One type of cancer that causes death in the male population is prostate cancer. This disease occurs only in men because in women they do not have a prostate appearance. The aim of this study was to compare the accuracy of the model with the predictions of prostate cancer specialists. Prediction is made based on prostate specific antigen data, age, and patient prostate volume. The independent variables in this study were prostate specific antigen, age, and prostate volume. The dependent variable is the risk of prostate cancer using a fuzzy model. The novelty of this study is that the model has a low, moderate, high, and very high prostate cancer risk level output. In the previous article only PCR values were produced. The results show that the proposed fuzzy model provides a PCR value that is within the PCR interval predicted by a specialist doctor can be used properly to help diagnose and analyze the possibility of prostate cancer and is one of the considerations for doctors to decide whether or not a biopsy is needed for these patients.