Generally, medical diseases can be identified based on their symptoms already derived. Most of the medical diseases are not new and the symptoms are already plotted with results. The diseases like COVID19 are new and it is still in the observation stage. Whenever the symptoms are conceivable such as, the demand for automation in prediction exists. Such demand leads to the development of automated medical care machine which can deliver the suggestions or prescriptions in absence of doctors due time or place constraints (now it is higher due to COVID19 pandemic). In a few situations, doctors can also help patients with live video streaming assist mechanism. The automated machine can also produce the required medicine as per the basic needs. Many research papers are coming up on this aspect now a day. It is important to focus on this medical need on the way of researches done and the room to improve further shortly. When dealing with such automated prediction, the previous predictions and results happened should be taken into considerations. In such case, the big data with machine learning algorithms play a vital role in this process. In this article, the best-fit machine learning algorithm was identified for medical-related data sets. © 2021 Elsevier B.V., All rights reserved.