Comparative study of Artificial Intelligence techniques for the diagnosis of diseases.

Abstract

The diagnosis of diseases is a complex cognitive process that involves training, experience, pattern recognition and calculation of conditional probability, among other less understood components. In recent decades, several efforts have been made to apply predictive analysis in health systems and to launch machine learning systems to facilitate the diagnosis of diseases. Considerable advances are currently used, especially the application of Artificial Intelligence (AI) techniques; feasible when they take advantage of available data and clinical experience. This paper aims to compare AI techniques to select the one that best fits the diagnosis of diseases, when there are stored data on the behavior of diseases that frequently affect the population.