Early Detection Software for Diabetes Retinopathy

Abstract

It has been claimed that technology utilized in laboratories does not directly translate to healthcare. Over the last few years, research into the application of Artificial Intelligence (AI) in the diagnosis of Diabetic Retinopathy (DR) has exploded, but little of that information has been translated into practice to aid people in need.One argument is that it is a new area with untested technologies that is changing far too quickly. Furthermore, the Real Healthcare situation can be extremely difficult, posing several challenges ranging from rigorous restrictions to population heterogeneity. A workable solution must meet all of these issues, including ethics, standards, and any security risks. It's also worth noting that existing AI is limited to a few restricted applications and may struggle to grow when faced with problems of varying complexity. A patient with DR, for example, may have other health issues such as glaucoma or cataracts. DR has been a primary cause of blindness for millions of people around the world, and because it is difficult to diagnose when it is treatable, early eye screening is the cure. In this study, we aim to combine Artificial Intelligence with other technologies to provide a low-cost Diabetic Retinopathy diagnosis while also attempting to overcome existing barriers to widespread eye screening adoption