Artificial neural network as classification method for prostate cancer incidence. (2017)

• Record Type: Journal Article
• Authors: Alqahtani, Khaled S.; Srinivasan, Shankar; Mital, Dinesh P.
• Is Part Of: International journal of medical engineering and informatics. Volume 9:Number 1(2017)
• Page Start: 61
• Page End: 72
• Publication Date: 2017
• Subjects: prostate cancer -- prostate-specific antigen -- artificial neural networks -- ANNs -- logistic regression -- decision tree classifier -- support vector machines -- SVM -- cancer prediction; 610.2805
• Languages: English
• ISSNs: 1755-0653

Abstract

This study uses artificial neural network (ANN) classification method to predict the occurrence of prostate cancer. The surveillance, epidemiology, and end results (SEER) program data, for the years 2004 to 2011, was used to train and test the performance of ANN. In addition, ANN model's result was compared with the most used classification methods. The result of classification methods' tests showed that the artificial neural network had success rates of 99.36% compared to logistic regression (84.95%), decision tree classifier (90.34%) and support vector machine (88.52%).