Diagnosis of Progressive Optic Neuropathy Disorder Using Machine Learning Classifiers

Abstract

Optic neuropathy disorder, popularly known as glaucoma, is one of the prevalent diseases which leads to permanent vision loss. Globally, there are more than 60 million people are suffering from this disease, and early detection could help people from vision loss. In recent years, machine learning-based models gained popularity for medical diagnosis. This paper discusses the identification of glaucoma from visual field test parameters using machine learning classifiers. Six classifiers were implemented for the experiment, and these models were trained based on multiple input parameters, SVM shown strong, reliable prediction capability for the right diagnosis of glaucoma.