A SURVEY ON IDENTIFICATION OF DIABETIC RETINOPATHY FOR MEDICAL DIAGNOSIS

Diabetic retinopathy is a complication of diabetes, which causes damage to the retina as well as other very small blood vessels located throughout the body (DR). Deterioration in the development of the retina is one of the symptoms that may be seen with this condition. There is an increased risk of being completely blind as diabetic retinopathy worsens over time. In light of the aforementioned circumstances, it is more important than ever before to perform an early diagnosis of diabetes and diabetic retinopathy in order to identify the damaged lesions and offer the diabetic patients with the appropriate counseling and therapy. DR may be identified by hand or automatically, depending on your preference. Both strategies might be considered viable options. Optometrists and ophthalmologists are the ones who actually do the manual operation; they are also the ones who give evaluations and reasons for it. It takes a significant amount of time, and expensive equipment is necessary. Automated systems that use artificial intelligence and deep learning rather than more traditional methods would be able to recognise DR at an earlier stage of the automation problem. The bulk of the research that has been conducted has focused on the importance of diagnosing DR at an early stage. This article gives an overview of automated DR detection techniques by focusing on two essential properties of fundus pictures and DR detection strategies. Both of these topics are discussed in the essay. The following constitutes each of these components: This article describes a number of challenges that aspiring academics face, as well as the discoveries that were made by those who came before them.