Diabetic retinopathy causes the life of eye decay considerably. There are stages associated with the DR. Early detection of DR could lead to the adverse affect of DR to be minimised. Techniques have been devised to tackle and identify the problems of DR at early stage. This paper presents the comprehensive review of techniques such as machine learning and deep learning, used for the purpose of detection of DR and also performs the comparative analysis of parameters used for the same. The proposed algorithm uses MSVM algorithm that discovers more patterns to detect disease accurately. The results will help in predicting quicker and more accurate disease so that it lead timely treatment of the patients.

Diabetic retinopathy, machine learning, deep learning, datasets

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