Evaluation of Prostate Cancer via Machine Learning

Authors : Fatma Söğüt, Evrim Ersin Kangal

Pages : 274-281

Doi:10.29132/ijpas.1382974

View : 65 | Download : 73

Publication Date : 2023-12-31

Article Type : Research Paper

Abstract :By training computers with machine learning technique, patients can be prevented from being exposed to unnecessarily difficult examinations. In recent years, machine learning-based disease assessment approach has gained importance in terms of the benefits it provides to clinical methods. There is a remarkable increase in studies in this direction. There are a limited number of clinical guiding parameters in predicting some types of cancer, and this limitation pushes the patients under treatment to a very frustrating process. For this reason, apart from ordinary procedure of the traditional medicine, an alternative approach to predict the any type of cancer is making a computer-based evaluation that has become a highly studied method in recent years. In this study, a machine learning (ML) approach will be used to evaluate prostate cancer, which is the second most common cancer-related death in men worldwide. For this purpose, the K-Nearest Neighbor (kNN) algorithm based on ML will be used with feature selection, which is a dimension reduction technique. An open source database, Kaggle, was used for the evaluation. The accuracy value of the used algorithm was found 88%.
Keywords : Prostat kanseri, makine öğrenimi, özellik seçimi, kNN