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In recent years, huge amounts of structured, unstructured, and semi-structured data have been generated by various institutions around the world and, collectively, this heterogeneous data is referred to as big data. The health industry sector has been confronted by the need to manage the big data being produced by various sources, which are well known for producing high volumes of heterogeneous data. Various big-data analytics tools and techniques have been developed for handling these massive amounts of data, in the healthcare sector. In this paper, we discuss the impact of big data in healthcare, and various tools available in the Hadoop ecosystem for handling it. We also explore the conceptual architecture of big data analytics for healthcare which involves the data gathering history of different branches, the genome database, electronic health records, text/imagery, and clinical decisions support system.


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Big Data Analytics for Healthcare Industry: Impact, Applications, and Tools

Show Author's information Sunil Kumar( )Maninder Singh
Directorate of Livestock Farms, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, India.
Department of Computer Science, Punjabi University, Patiala, India.

Abstract

In recent years, huge amounts of structured, unstructured, and semi-structured data have been generated by various institutions around the world and, collectively, this heterogeneous data is referred to as big data. The health industry sector has been confronted by the need to manage the big data being produced by various sources, which are well known for producing high volumes of heterogeneous data. Various big-data analytics tools and techniques have been developed for handling these massive amounts of data, in the healthcare sector. In this paper, we discuss the impact of big data in healthcare, and various tools available in the Hadoop ecosystem for handling it. We also explore the conceptual architecture of big data analytics for healthcare which involves the data gathering history of different branches, the genome database, electronic health records, text/imagery, and clinical decisions support system.

Keywords:

big data, healthcare, Hadoop, MapReduce
Received: 16 May 2018 Accepted: 02 August 2018 Published: 15 October 2018 Issue date: March 2019
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Publication history

Received: 16 May 2018
Accepted: 02 August 2018
Published: 15 October 2018
Issue date: March 2019

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