Dynamical model of Tuberculosis-Multiple Strain Prediction based on artificial neural network

Abstract

This paper presents implemented artificial neural network (ANN) for diagnosing pulmonary tuberculosis progression and dynamics. Tuberculosis is an infectious disease caused in most cases by microorganism, called Mycobacterium tuberculosis. Tuberculosis is a huge problem in most low-income countries, and also in the Balkan region. The design of the artificial neural network is based on two strains of tuberculosis bacteria and multiple strains of tuberculosis. Training data sets contain 1000 reports for this artificial neural, 800 of them are used for estimation and 200 for validation. The ANN system is validated on 1400 patients from the Clinical Centre University of Sarajevo in the two years period. Out of 1315 patients, 99.24% are correctly classified as tuberculosis related patients. System was 100% successful on 85 patients were diagnosed with normal lung function. Sensitivity of 99.24% and specificity of 100% in tuberculosis classification are obtained. Our artificial neural network is a promising method for predicting diagnosis and possible treatment routine for tuberculosis disease.