Abstract:
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-of-the-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.