ABSTRACT
This chapter discusses the application of machine learning techniques in the healthcare sector for the prediction of epidemic disease outbreaks. Prediction is an important element in the decision-making processes for responding to and controlling any epidemic disease outbreak. Recently, a large number of countries across the globe has experienced coronavirus infectious disease outbreaks. Machine learning techniques can be very helpful for predicting and managing such epidemic outbreaks. In the new era of artificial intelligence, there exist huge opportunities for technology to be involved to assist in the monitoring and controlling these types of epidemics. With the growth of big data in the healthcare and biomedical sectors, it is now viable to exploit machine learning techniques and accurate disease prediction models to markedly improve epidemic prediction, which will ultimately help in the prevention and control capabilities. This chapter examines the variety of machine learning models that have been developed to predict epidemic diseases and shows how machine learning techniques can be of importance to the public health practitioners for predicting and detecting disease spread, improving epidemic management, and reducing the impact of outbreaks. It also highlights how machine learning techniques can be used for containing the current outbreak of COVID-19, which spread across the globe within a short period of three to four months.
