In the present era of Fourth Industrial Revolution, the automation of digital world has abundant data on health care such as Electronic Health Records (EHR), clinical trials, relational databases. For quick perception of these data and to mechanize the enhanced applications, familiarity with Artificial Intelligence (AI), specifically Machine Learning (ML) is a way. It cannot succeed a human treatment, but can mark the better solutions for health problems. With phenomenal execution machine learning and deep learning mechanisms in the recent times distinguished and invoked on various real time health care applications to examine and detect the treatment in health industry the effectiveness of ML. In this paper we examined the illnesses like Lung cancer, Alzheimer’s Disease, COVID-19, cervical cancer was implemented using AdaBoost algorithm with eNose, Reinforcement Learning, Bayesian Belief Network and Principal Component Analysis (PCA) with genetic algorithm, respectively. However, we also implemented some random machine learning algorithms on symptoms2disease dataset and unveiled some remarkable outcomes. Furthermore, we probe the challenges, barriers and favorable circumstances in the field of healthcare through state of art machine learning mechanisms. Based on relevant research, this paper aims to find out the quality and novelty in health care and facilitates how machine learning (ML) is being used to help in the early identification of numerous diseases and to take efficient decision support for medical applications.