Prediction of Multi Drug Resistant Tuberculosis using Machine Learning Techniques

Abstract

Mycobacterium Tuberculosis bacteria is the primary cause for Tuberculosis. TB is one of the main reasons of mortality around the world. Multi Drug Resistant Tuberculosis (MDR-TB) is a type of tuberculosis bacteria which are resistant to anti-TB drugs, drugs like isoniazid (INH) and rifampin (RMP). Different Machine learning approaches has been widely applied to predict MDR TB. Here, we review different Machine Learning Approaches to predict MDR-TB. Different feature estimation methods, execution of distinct machine learning models also have been explored. Additionally, the utilization of the distinctive machine learning system models for distinguishing the dis-functionalities of MDR-TB in the recent decades has been talked about.