DIAGONOSIS OF DIABETIC RETINOPATHY DETECTION SYSTEM

ABSTRACT In the given literature, Diabetic Retinopathy (DR) is normally identified as a very serious eye-related condition of diabetes mellitus and as a severe cause of blindness that is very easy to avoid throughout the world at large. The latest research imparts a completely automated Diabetic Retinopathy Detection System, which is built on deep-learning structures, along which convolutional Neural Networks (CNNs) stand alone. It is a tool used to convert 2D retinal fundus pictures to labels pointing out the availability and intensity of DR and these results of the diagnosis are placed along a continuum that ranges between no DR to proliferative DR. Its use with enabled AI systems has also proven to diagnostically accurate helping to point out the ability of this type of system to enhance conventional clinical processes and lower dependence on interpretations of a manual nature. Even though, it is not actually meant to replace the professional opinion of the ophthalmologist, the platform will give a low-cost ,scalable method of early screening in the most efficient way possible and reducing the potential of vision impairment in patients that are diabetic eventually