Artificial intelligence tries to imitate human intelligence with powerful
computer skills and aims to solve the problems that people have difficulty solving.
Therefore, artificial intelligence and machine learning have begun to be applied
thoughtfully in the field of healthcare and other lives. Remarkable results have been
obtained in the performed research. These results have paved the way for applications
in different healthcare areas and increase the frequency of the studies to achieve even
more successful results in the same field. Prediction applications of machine learning
are widely applied in healthcare as both class prediction and regression and support
doctors and independent decision-making mechanisms. Even if classification studies of
these applications have been performed, their diversity and excess numbers make them
difficult and cause them to be considered on a subject basis. In this chapter, the usage
of the terms “prediction,” “regression,” and “classification” in the literature is
explained, and evaluation metrics used in all kinds of problem domains are defined. In
addition to these, the problem areas of using machine learning techniques are
summarized, and the literature search is performed in three scientific databases.
Finally, the number of publications in the considered databases and an overview of the
healthcare examples are presented. The data obtained and presented show that the
applications using machine learning continue to increase significantly in healthcare and
continue to be applied unlimitedly in all healthcare problems.
Keywords: Artificial intelligence, Classification, Evaluation metrics, Healthcare,
Literature search, Machine learning algorithms, Machine learning, Prediction
applications, Prediction, Regression.
