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Abstract-Automated screening of diabetic retinopathy plays an important role in diagnosis of the disease in early stages and preventing blindness in patients with diabetes. Various machine learning approaches have been studied in literature with the purpose of improving the accuracy of the screening methods. In this study a comparative analysis of nine common classification algorithms is performed to select the most applicable approach for the specific problem of screening diabetic retinopathy patients.