Taxonomy on Healthcare System Based on Machine Learning Approaches: Tuberculosis Disease Diagnosis

This study enlightens the impact of Machine Learning algorithms and practices in the context of Healthcare Informatics. In the domain of Healthcare Informatics (HI), Machine Learning (ML) procedures have been classified into four classes named as ML-HI types, ML-HI approaches, ML-HI paradigms and ML-HI algorithms. In this study, we provide an overview of the state-ofthe-art, the research challenges, and the forthcoming directions, specifically driven to the diagnosis of Tuberculosis (TB) disease. Moreover, we introduce our proposed framework for TB diagnosis disease based on ML. We emphasized the strengths and weaknesses of the studied methods facilitate to the aid analysis community to pick the suitable technique to use within the Healthcare Informatics domain.