DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY USING MACHINE LEARNING
Aryan Kokane1, Gourhari Sharma1, Akash Raina1, Shubham Narole1, Prof. Pramila M. Chawan2
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The objective of this paper is to perform a survey of different literatures where a comprehensive study on Diabetic Retinopathy (DR) is done and different Machine learning techniques are used to detect DR. Diabetic Retinopathy (DR) is an eye disease in humans with diabetes which may harm the retina of the eye and may cause total visual impairment. Therefore it is critical to detect diabetic retinopathy in the early phase to avoid blindness in humans. Our aim is to detect the presence of diabetic retinopathy by applying machine learning classifying algorithms. Hence we try and summarize the various models and techniques used along with methodologies used by them and analyze the accuracies and results. It will give us exactness of which algorithm will be appropriate and more accurate for prediction.