Analysis of diabetic retinopathy diagnosis using learning based algorithm

Diabetic Retinopathy is one of the most dangerous disease and should be identified and treated properly at the very early stage. This is usually diagnosed by scanning the interior structure of human eye with modality like optical coherence tomography and color fundus photography. Then the disease is been diagnosed manually by the respective experts which is a time-consuming process. This process should be automated so that the disease can be diagnosed in a faster and efficient way to reduce the human error. More number of researchers have been done based on automating the diagnosing of diabetic retinopathy disease using machine learning and deep learning approach. The most recent and robust techniques are been discussed in this paper.