Knowledge has been increasingly seen as a key competitive resource in organizations and this has influenced selection and recruitment practices in many organizations. Today, it is an essential necessity for healthcare organizations to manage both tacit and explicit knowledge effectively in order to provide the best possible healthcare by solving problems and making the most ideal and flawless. In addition, knowledge engineering is an intelligent process by which the gathered raw health data is transformed into knowledge in order to be used for "integrate and interpret knowledge for individualized healthcare". Knowledge engineers use artificial intelligence (AI) concepts and techniques in developing knowledge-based systems. Likewise, machine learning is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to "learn from health data", without being explicitly programmed. During the past few years, with the advances in machine/deep learning, many new computation models have been proposed and significantly applied in Natural Language Processing, Neuroscience, Biomedical, Internet of Medical Things, Chronic Diseases, Epidemiology, etc.