Eye refractive error classification using machine learning techniques

Abstract

Machine learning is a subdivision of Artificial Intelligence (AI) that is concerned with the design and development of intelligent algorithms that enables machines to learn from data without being programmed. Machine learning mainly focus on how to automatically recognize complex patterns among data and make intelligent decisions. In this paper, intelligent machine learning algorithms are used to classify the type of an eye disease based on ophthalmology data collected from patients of Mecca hospital in Sudan. Three machine-learning techniques are used to predict the severity of the eye that occurred during the investigation, which are Naïve Bayesian, SVM, and J48 decision tree. The obtained result showed that J48 classifier outperforms both Naïve Bayesian as well as SVM.