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The application of Big Data in medicine: current implications and future directions

Overview of attention for article published in Journal of Interventional Cardiac Electrophysiology, January 2016
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Title
The application of Big Data in medicine: current implications and future directions
Published in
Journal of Interventional Cardiac Electrophysiology, January 2016
DOI 10.1007/s10840-016-0104-y
Pubmed ID
Authors

Christopher Austin, Fred Kusumoto

Abstract

Since the mid 1980s, the world has experienced an unprecedented explosion in the capacity to produce, store, and communicate data, primarily in digital formats. Simultaneously, access to computing technologies in the form of the personal PC, smartphone, and other handheld devices has mirrored this growth. With these enhanced capabilities of data storage and rapid computation as well as real-time delivery of information via the internet, the average daily consumption of data by an individual has grown exponentially. Unbeknownst to many, Big Data has silently crept into our daily routines and, with continued development of cheap data storage and availability of smart devices both regionally and in developing countries, the influence of Big Data will continue to grow. This influence has also carried over to healthcare. This paper will provide an overview of Big Data, its benefits, potential pitfalls, and the projected impact on the future of medicine in general and cardiology in particular.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 195 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Unknown 194 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 39 20%
Researcher 22 11%
Student > Ph. D. Student 20 10%
Student > Bachelor 19 10%
Student > Doctoral Student 11 6%
Other 34 17%
Unknown 50 26%
Readers by discipline Count As %
Computer Science 35 18%
Medicine and Dentistry 28 14%
Business, Management and Accounting 14 7%
Social Sciences 10 5%
Engineering 10 5%
Other 38 19%
Unknown 60 31%