Abstract
Diabetic Retinopathy (DR) is a diabetic-induced eye disorder that can lead to vision loss or even total blindness. For people aged 20 to 64 years, diabetic retinopathy accounts for 12 percent of all new cases of blindness in the United States and is the leading cause of blindness. If caught early enough, progression to vision impairment may be delayed if not fully prevented, but this is often difficult because symptoms can occur too late to provide successful care. It has been estimated that diabetic retinopathy affects about 93 million people worldwide, though only half are aware of it. Diabetic Retinopathy has four major stages; dysfunctional blood vessels propagate on the surface of the retina at its most advanced level, which can lead to scarring and loss of cells in the retina. This paper explains how we are going to identify whether a patient is affected by Diabetic Retinopathy (DR) or not by using their retina image. This paper describes the step-by-step process to build the model, it includes the Image dataset and pre-processing, split the training and test data set, train the model, and validate the model.
Citations
IRE Journals:
Balachandar Jeganathan
"Diabetic Retinopathy Detection" Iconic Research And Engineering Journals Volume 8 Issue 4 2024 Page 171-179
IEEE:
Balachandar Jeganathan
"Diabetic Retinopathy Detection" Iconic Research And Engineering Journals, 8(4)
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