Covid-19 and Diabetic Retinopathy (Dr) Detection Using Ai & Deep Learning

Abstract

Artificial intelligence (AI), deep learning (DL), and neural networks (NN), though these words sound flashy and may leave you perplexed, represent powerful technologies that have the capabilities to transform the world. It is just now emerging how valuable these machine learning-based techniques are and how they can solve many real-world problems ranging from fraud detection, resource management to driver-less cars.One such field where the application of AI systems is progressively growing is in medical diagnosis. A lot of research is going on to enhance computer-aided diagnosis and detection of diseases. Recent world events have tested the healthcare systems all around the world. Suppose we have sophisticated deep learning systems (DLS) that could help in faster and efficient disease detection and diagnosis; how beneficial it would be to assist both medical professionals and patients.This study explores how AI and machine learning techniques could be used for disease detection, giving COVID-19 and Diabetic Retinopathy detection examples. We present two deep learning (DL) models, one to detect COVID-19 from chest x-ray image scans and the other to detect Diabetic Retinopathy at various stages of the disease from retinal fundus images. With reasonably high accuracy, >95% for the COVID-19 detection model and >80% for the Diabetic Retinopathy detection model, these results highlight AI and deep learning potential to assist general practitioners.