ABSTRACT
Machine learning (ML) has attracted significant interest toward developing smart healthcare systems by providing intelligent clinical decision making especially on disease assessment and its associated risk prediction. This chapter focuses on discussing the basics of the methodology of the ML approach for disease assessment and it also highlights different assessment aspects. In supervised learning, there are two types of predictions—classification and regression. In the medical field, unsupervised learning is very effective in tissue differentiation. It can be used to decern different types of tissues at a certain place in the body. Diseases can happen to any person at any time. It can transmit via viruses, bacteria or can even occur genetically. The application of ML in the medical field is enormously visible in recent days. As the capability of storing and processing data is ever-increasing, the use of ML is also increasing.
