title: 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.
authors: Department of Computer Engineering, Sakarya University, 54187, Adapazari, Turkey. erhanelveren@duzce.edu.tr
authors: Erhan
authors: E
authors: Elveren
authors: Nejat
authors: N
authors: Yumuşak
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical; D055614:Genetic Phenomena; D006801:Humans; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D014376:Tuberculosis / Q000175:diagnosis* / Q000235:genetics; D014421:Turkey