ABSTRACT
Healthcare as a sector has seen a phenomenal overhaul in the past centuries, and has been one of the fastest growing sector. With the enormous amount of data generated and used in healthcare, machine learning, which at its core is a data-driven domain, provides myriad technological innovations and applications. This chapter aims to give an overview of the basics of machine learning, evaluates its importance of use over the statistical methods and provides brief information about different machine learning techniques. It demonstrates the key segments of healthcare, which in itself is a multidisciplinary industry. Further, the chapter gives a broad coverage about the numerous application of machine learning in prognosis and medical diagnosis. Electronic health records (EHRs), which are an important application in a smart healthcare setup, have the potential to aid better management of medical systems is cited and the proliferation of EHRs in various clinical applications can provide better clinical decision support. This chapter encapsulates application of machine learning in medical image analysis and natural language processing (NLP) of medical documents and literature. Machine learning in healthcare can be used for combatting the pandemic at both levels of primary prediction and for post-pandemic control. The main objective of this chapter is to help the researchers in this field to get a comprehensive overview of the machine learning applications in healthcare. This chapter also highlights the integration of machine learning with cutting-edge technologies like big data and Internet of Things “IoT”, biometrics and cloud computing, which have the potential to provide remarkable results and carve a new path for smart healthcare.
