Tuberculosis Disease Classification Using Genetic-neuro Expert System

This study investigates the application of the hybrid technique Genetic-Neuro approach for Tuberculosis disease classification. Evolutionary algorithms are proved to be the efficient methods for optimization problems and their primary component namely Genetic Algorithm is used to select the significant features for Disease Classification. Artificial Neural Network is used for classification and the training is done by methods like Levenberg Marquardt algorithm. The construction process of the system is illustrated by using tuberculosis disease data. The results reveal that the hybrid technique Genetic-Neural system outperforms the conventional technique Artificial Neural Network for disease classification.