  In this chapter, we provide a brief overview of applying machine learning
techniques for clinical prediction tasks. We begin with a quick introduction to
the concepts of machine learning and outline some of the most common machine
learning algorithms. Next, we demonstrate how to apply the algorithms with
appropriate toolkits to conduct machine learning experiments for clinical
prediction tasks. The objectives of this chapter are to (1) understand the
basics of machine learning techniques and the reasons behind why they are
useful for solving clinical prediction problems, (2) understand the intuition
behind some machine learning models, including regression, decision trees, and
support vector machines, and (3) understand how to apply these models to
clinical prediction problems using publicly available datasets via case
studies.
