Title:

Real-Time Diabetes Retinopathy Monitoring IoT Device with Machine Learning

Diabetic retinopathy (DR) is the leading cause of blindness worldwide. It is estimated that more than 105 million people have been affected. When high blood sugar damages blood vessels in the retina, a layer of light-sensitive cells at the back of the eye, Damaged blood vessels can swell and leak, causing blurred vision or stopping blood flow. Sometimes new blood vessels grow, but they are abnormal and can lead to further vision problems. This project shows how we can use a tiny device with machine learning capabilities to monitor the retina of a diabetic patient in real-time. We will use two main machine learning algorithms to improve the accuracy of test results.

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