Implications of big data analytics in developing healthcare frameworks – A review

The domain of healthcare acquired its influence by the impact of big data since the data sources involved in the healthcare organizations are well-known for their volume, heterogeneous complexity and high dynamism. Though the role of big data analytical techniques, platforms, tools are realized amon...

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Bibliographic Details
Main Authors: Venketesh Palanisamy, Ramkumar Thirunavukarasu
Format: Article
Language:English
Published: Elsevier 2019-10-01
Series:Journal of King Saud University: Computer and Information Sciences
Online Access:http://www.sciencedirect.com/science/article/pii/S1319157817302938
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Summary:The domain of healthcare acquired its influence by the impact of big data since the data sources involved in the healthcare organizations are well-known for their volume, heterogeneous complexity and high dynamism. Though the role of big data analytical techniques, platforms, tools are realized among various domains, their impact on healthcare organization for implementing and delivering novel use-cases for potential healthcare applications shows promising research directions. In the context of big data, the success of healthcare applications solely depends on the underlying architecture and utilization of appropriate tools as evidenced in pioneering research attempts. Novel research works have been carried out for deriving application specific healthcare frameworks that offer diversified data analytical capabilities for handling sources of data ranging from electronic health records to medical images. In this paper, we have presented various analytical avenues that exist in the patient-centric healthcare system from the perspective of various stakeholders. We have also reviewed various big data frameworks with respect to underlying data sources, analytical capability and application areas. In addition, the implication of big data tools in developing healthcare eco system is also presented. Keywords: Big data, Healthcare, Framework, Infrastructure, Analytics, Patterns, Tools
ISSN:1319-1578