Tuberculosis Disease Diagnosis Using Artificial Neural Network Trained with Genetic Algorithm

Abstract

Tuberculosis is a common and often deadly infectious disease caused by mycobacterium; in humans it is mainly Mycobacterium tuberculosis (Wikipedia 2009). It is a great problem for most developing countries because of the low diagnosis and treatment opportunities. Tuberculosis has the highest mortality level among the diseases caused by a single type of microorganism. Thus, tuberculosis is a great health concern all over the world, and in Turkey as well. This article presents a study on tuberculosis diagnosis, carried out with the help of multilayer neural networks (MLNNs). For this purpose, an MLNN with two hidden layers and a genetic algorithm for training algorithm has been used. The tuberculosis dataset was taken from a state hospital's database, based on patient's epicrisis reports.