A Machine Learning-Based Prediction Model for Prostate Cancer (Proposed)

Abstract

Prostate cancer is an aging disease that can occur in any part of the prostate gland. It is a leading cause of death in men globally. In Nigeria, prostate cancer is the most common cancer particularly in North Central Nigeria. Hence there is need to develop machine learning prediction models to predict the disease occurrence using it's prognostic factors so as to adopt lifestyles that hinder prostate cancer development in the body. Different machine learning techniques have been adopted for prostate cancer detection through training and testing on different datasets. This work proposes the use of three (3) machine learning algorithms namely naive bayes, k-nearest neighbor and decision trees for the prediction of prostate cancer using locally sourced dataset in North central Nigeria. This is aimed at determining the best prediction from these algorithms. The result will assist in adopting the best approach for accurate disease prediction thereby saving lives and increasing life expectancy in males.