Abstract
Cataract, glaucoma, and retinal disorders in individuals are the three main causes of vision impairment globally. The rising prevalence of these diseases necessitates an immediate, accurate diagnosis. The suggested approach is created and designed to make it simple for individuals to diagnose illnesses of the retina, glaucoma, cataract and many more. For the categorization and localization of eye disorders, artificial neural networks and convolutional neural networks are employed. The suggested approach will reduce the amount of brought-on blindness by enabling patients to receive the necessary care for the mentioned illnesses at an early stage. The adopted approach evaluates the effectiveness and safety of cataract surgery in eyes with age-related macular degeneration in addition to the diagnosis of glaucoma and retinal diseases. The accuracy of algorithms is demonstrated in this study using images of the fundus from healthy eyes as well as eyes with glaucoma, cataracts, and retina. Nowadays, the concept of categorizing photographs based on their fundus and extracting features is well recognized, and it also plays a crucial role in the conclusion.
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