Classification of tb disease diagnosis using anfis

Symptoms based diagnosis of a disease is one of the challenging tasks in the medical field. Several techniques are available for classification. In this paper,used ANFIS for classification of TB disease on the available data. Hybrid system is a learning algorithms that utilizes the training and learning networks to find parameters of a fuzzy system based on the symptoms created by the mathematical model. In this paper, an expert system is proposed to detect the Tuberculosis disease, which are very common and important disease using an adaptive neuro-fuzzy inference system (ANFIS). The main objective of this study is classification of Tuberculosis disease based on the symptoms. The dataset for the training of an ANFIS is collected from the various physicians for the classification of TB disease. Finally obtained the accuracy of classification result is 89%.