Diabetic retinopathy detection using a pretrained machine learning model

One of the possible side effects of diabetes is Diabetic Retinopathy. Early diagnosis of diabetic retinopathy is an important step toward healing and can prevent many patients from potential blindness. To identify diabetic retinopathy, practitioners may need an artificial intelligence tool to provide a second opinion to confirm or refute a diagnosis. In this article we use a pretrained machine learning model to find a solution to the issue of low-quality inputs by implementing, in the pre-processing step, the technique of Contrast Limited Adaptive Histogram Equalization to extract more features especially the blood vessels.