Evolution and Tendency on the Feature Extraction Process for Diagnostic Aid in Healthcare

Abstract

Diagnostic support systems based on artificial intelligence are of great interest in the field of healthcare since they offer an early and highly accurate diagnosis. In recent years, the use of machine learning models that are less complex than the most widely used ones, such as deep neural networks, has been of interest. For this purpose, it is necessary to apply previous steps of feature extraction of different types, according to the problem that has to be solved. In this chapter, the authors intend to provide an overview of the current panorama of these systems, differentiating between those that extract features and those that do not. An exhaustive analysis is made of the works carried out in the last five years, checking the artificial intelligence models used, the features extracted, and the countries responsible for each work.