In Today's world, disease diagnosis plays a vital role in the area of medical imaging. Medical imaging is the method and procedure of making visual descriptions of the interior of a body for clinical investigation and clinical mediation, as well as visual depiction of the function of some organs or tissues. Medical imaging also deals with disease detection. We can get a better view of detecting the disease by using machine learning in medical imaging. So Now what is Machine Learning (ML)? ML is an artificial intelligence (AI) utilization that presents the system with the capacity to learn and develop itself. It mainly focuses on the development of computer programs that can access the data and use it for themselves. In this chapter we will focus on detection Diabetic retinopathy using machine learning. Diabetes is a type of disease that result in too much sugar in blood. There are three main types of diabetes. Diabetic retinopathy is one of them. Diabetic retinopathy is an eye infection brought about by the inconvenience of diabetes and we ought to recognize it right on time for effective treatment. As the disease advances, the sight of a patient may begin to break down and lead to diabetic retinopathy. Thus, two groups were recognized, in particular non‐proliferative diabetic retinopathy and proliferative diabetic retinopathy. We should detect it as soon as possible as it can cause permanent loss of vision. By using ML in medical imaging we can detect it much faster and more accurately. In this chapter we will analyze about different ML technologies, algorithms and models to diagnose diabetic retinopathy in an efficient manner to support the healthcare system.