WITHDRAWN: Extensive analysis of machine learning algorithms to early detection of diabetic retinopathy

Abstract

Abstract In Today’s world, disease diagnosis plays a vital role in the area of medical imaging. Medical imaging is the method and procedure of making visual descriptions of the interior of a body for clinical investigation and clinical mediation, as well as visual depiction of the function of some organs or tissues. Medical imaging also deals with disease detection. Better view is obtained to detect the disease by using machine learning in medical imaging. Machine Learning (ML) is an artificial intelligence (AI) utilization that presents the system with the capacity to learn and develop itself. It mainly focuses on the development of computer programs that can access the data and use it for themselves. In this work the focus will be on detection of Diabetic retinopathy using machine learning. Diabetes is a type of disease that results in too much sugar in blood. Diabetic retinopathy is one of the main side effects of diabetes. Diabetic retinopathy is an eye infection brought about by the inconvenience of diabetes and it is needed to be recognized right on time for effective treatment. As the disease advances, the sight of a patient may begin to break down and leads to diabetic retinopathy. It should be detected as soon as possible as it can cause permanent loss of vision. Thus, two groups were recognized, in particular non-proliferative diabetic retinopathy and proliferative diabetic retinopathy. Diabetic retinopathy could be detected much faster and more accurately by using ML in medical imaging. In this work, different ML technologies, algorithms and models will be analyzed to diagnose diabetic retinopathy in an efficient manner to support the health care system.