Trends and Techniques of Handling Big Health Data
S.Aarathi1, K.Bala Chowdappa2, K.Sudhakar3
1S.Aarathi, Assistant Professor, G.pulla Reddy Engineering College, Kurnool (Andhra Pradesh), India.
2K.Bala Chowdappa, Assistant Professor, G.pulla Reddy Engineering College, Kurnool (Andhra Pradesh), India.
3K.Sudhakar, Assistant Professor, G.pulla Reddy Engineering. College, Kurnool (Andhra Pradesh), India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 22 June 2019 | PP: 798-804 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C11690283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The current trend of society generates torrents of data across various sources like social networking, health sectors, mobile sensors, industries. This voluminous data raised a scope for uncovering hidden insights of this data. This huge data often called big data could undergo several data analytics to retrieve the unnoticed patterns, trends, associations, querying, and information security. Here, in this paper we focus on health care industry towards applying analytics on the health data like EHR’s, medical images, reports, sensors and transform this data to make out a meaningful outcome that helps towards diagnosis and prognosis at an early intervention which reduces the morbidity, sensitizing the adverse effects of infectious diseases[2]. We also discuss the existing mechanisms of handling health care data and its underlying effects that are to be tackled.
Keywords: Big Data, EHR, Data Analytics, Predictive Analytics, Hadoop, Data Visualization.
Scope of the Article: Big Data Networking