Early Identification of Diabetic Retinopathy Using Deep Learning Model: A Survey

Diabetes mellitus and its symptoms are causing severe and even life-threatening difficulties in the lives of people all over the world. A side effect of diabetes mellitus called diabetic retinopathy causes an eye condition that can impair vision. The important aspect of treatment is that if it is detected early, then disease progression can be slowed by controlling modifiable risk factors (such as blood glucose and blood pressure), and laser therapy or treatment with vascular endothelial growth factor inhibitors can be used to reduce the risk of visual loss. Early identification of diabetic retinopathy is aided by retinal screening. Recently, deep learning methods are becoming massively widely used to facilitate automatic retinal screening in the retina's fundus. Deep learning methods are more effective in the early detection of deep retinal retinopathy. To evaluate the effectiveness of deep learning approaches for detecting diabetic retinopathy, we conducted a systematic review, including a meta-analysis of distinct deep learning methods and several types of classifiers from some recent pertinent research work. This survey will be useful for technical people and academics who wish to strive to improve the diagnostics of a system that will be more powerful in practice.