Abstract

Diabetic retinopathy is one of the prevalent reasons of sight impairment in this day and age According to an epidemiology study, diabetic retinopathy affects one out of every three diabetics. In today's world, disease diagnosis is an essential part of medical imaging. In medical imaging, machine learning gives a greater vision for detecting disease. The objective is to detect diabetic retinopathy using ML. Machine learning in medical imaging could speed up and enhance the detection of sight caused by sugar. In order to detect diabetic retinopathy quickly and support the health-care system, this study will look at several machine learning methodologies, algorithms, and simulations. CNN is used to train the model.

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