Social media has enormously changed on how the cyber citizen reacts upon their health well-being. In some circumstances, the social media has given negative impact in healthcare industry whereby cyber citizens tend to participate in misleading advises regarding their health. The significance of initiating early disease prevention which has been addressed in Eleventh Malaysia Plan creates the opportunity in extending the knowledge of selfdiagnosis in health among Malaysian cyber citizens. However, there is still a challenge in benefiting social media for assisting early disease prevention due to lack of social presence in the social media content. There is a good opportunity in identifying predictive factors for social presence in social media as well as predicting self-diagnosis information during the early stage of disease prevention. Therefore, this paper aims at providing the comprehensive and detailed study on big data analytics in healthcare domain in four analytical methods including descriptive, diagnostic, predictive and prescriptive analytics. This paper describes the analytics in the four application areas; clinical support decision, healthcare administration, public health and drug design. A literature review has been adopted for this study by using online subscribed databases sources like Scopus and Science Direct and Web of Science databases. This paper will be able to produce literature analysis on analytics which are related to healthcare services as well as to see how it can contribute to the evolvement of the healthcare industry.
Volume 11 | 08-Special Issue
Pages: 1169-1179