The Use of Big Data Analytics in Medical Applications

Authors

  • Mahesh Babu Pasupuleti Data Analyst, Department of IT, TekSystems Inc, 200 S College St Suite 1200, Charlotte, NC 28202, USA

DOI:

https://doi.org/10.18034/mjmbr.v3i2.615

Keywords:

Medical Applications, Big Data Analytics, Healthcare System, Statistical Analysis

Abstract

The field of Big Data Analytics does not have a linear capacity for growth. It is based on a specified structure. Big data is now most useful for data backup purposes, rather than for anything else. Big Data is a collection of data sets that are both numerous and complicated in nature, and it is becoming increasingly popular. They consist of both organized and unstructured data that is constantly changing at a rate that is inconvenient for traditional relational database systems and existing analytical tools to keep pace with. There is constantly some new information being introduced. It also contributes to the resolution of India's major concerns. It also contributes to closing the data gap. Healthcare is the preservation or advancement of health by the prevention, interpretation, and medical treatment of the disorder, ill health, abuse, and other significant physical, mental, and spiritual degeneration in the mortal body. Health care is conveyed by health professionals in the form of unified health experts, specialists, physician associates, midwives, nurses, antibiotics, pharmacy, psychology, and other health-related fields of expertise. Additionally, it has an introduction, challenging elements and concerns, Big Data Analytics in use, technical specifications, research applications, industrial applications, and future applications. This article aims to provide knowledge in the field of big data analytics and its use in the medical arena.

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Published

2016-12-31

Issue

Vol. 3 No. 2 (2016): July - December Issue

Section

Peer-reviewed Article

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How to Cite

Pasupuleti, M. B. (2016). The Use of Big Data Analytics in Medical Applications. Malaysian Journal of Medical and Biological Research, 3(2), 111-116. https://doi.org/10.18034/mjmbr.v3i2.615
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