There have been very significant technological advancements made in the healthcare industry in recent decades. They have not only helped us better comprehend the morphology and physiology of the various organs that make up the human body but have also advanced the diagnosis and, consequently, the treatment of several diseases in a variety of medical specialties from very early stages. The advancements in artificial intelligence (AI) and computer vision (CV) have primarily made this possible. In a nutshell, these tools enable us to collect, process, interpret, and analyze a limitless quantity of static and dynamic medical data in real-time, which will improve the way each disease is characterized and the patients that are chosen. Many potentially fatal illnesses, such as COVID-19, pneumonia, and cancer, can be cured if diagnosed in the initial stages very early on. Computer-based medical imaging techniques, such as CT scans and X-rays, can be useful in detecting all of these illnesses. On the other hand, various brain anomalies and heart diseases can also be anticipated using biological signals, like electroencephalography (EEG), electrocardiogram (ECG) etc. Application of machine learning can make the predictions of these diseases more accurate. and help the clinician to detect appropriate ones. This helps in faster recognition of disease as well as with the intervention of the technology, makes it feasible to spread to remote places. The goal is to create machine learning algorithms that aid in the analysis of diverse medical data and the prediction of diseases based on the characteristics of the data.