The eyes may offer a "window into the soul," as poets say, but they also have a lot to say about your health. Dry eyes can be a sign of rheumatoid arthritis. High levels of cholesterol can cause a white, gray or blue ring to form around the colored part of your eye, called the iris. A coppery gold ring circling the iris is a key sign of Wilson's disease, a rare genetic disorder that causes copper to build up in the brain, liver and other organs, slowing poisoning the body. And that's not all: Damage to blood vessels in the back of your eye, called the retina, can be early signs of nerve damage due to diabetes, high blood pressure, coronary artery disease, even cancer, as well as glaucoma and age-related macular degeneration.
With the advancements in computer technology, there is a rapid development of intelligent systems to understand the complex relationships in data to make predictions and classifications. Artificail Intelligence based framework is rapidly revolutionizing the healthcare industry. These intelligent systems are built with machine learning and deep learning based robust models for early diagnosis of diseases and demonstrates a promising supplementary diagnostic method for frontline clinical doctors and surgeons. Machine Learning and Deep Learning based systems can streamline and simplify the steps involved in diagnosis of diseases from clinical and image-based data, thus providing significant clinician support and workflow optimization. They mimic human cognition and are even capable of diagnosing diseases that cannot be diagnosed with human intelligence. This paper focuses on the survey of machine learning and deep learning applications in across 16 medical specialties, namely Dental medicine, Haematology, Surgery, Cardiology, Pulmonology, Orthopedics, Radiology, Oncology, General medicine, Psychiatry, Endocrinology, Neurology, Dermatology, Hepatology, Nephrology, Ophthalmology, and Drug discovery. In this paper along with the survey, we discuss the advancements of medical practices with these systems and also the impact of these systems on medical professionals.