Machine learning classifiers for detection of glaucoma

Glaucoma is a disease that affects the optic nerve. This disease, over period of time, can lead to loss vision. Which known as ‘silent thief sight’. There are several methods in which be treated, if detected at an early stage It not possible for any technology, including artificial intelligence, replace doctor. However, it develop model based on classical image processing algorithms, combined with intelligence detect onset glaucoma certain parameters retinal fundus. would play important role detection and assist The traditional glaucoma, efficient they may be, usually expensive, machine learning approach diagnose from fundus images accurately classify its severity considered efficient. Here we propose support vector (SVM) method segregate, train models using high-end graphics processor unit (GPU) augment hull convex boost accuracy mechanisms along distinguishing different stages glaucoma. A web application screening process has also been adopted.