Big data analytics enhanced healthcare systems: a review

There is increased interest in deploying big data technology in the healthcare industry to manage massive collections of heterogeneous health datasets such as electronic health records and sensor data, which are increasing in volume and variety due to the commoditization of digital devices such as m...

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Bibliographic Details
Published in:The Journal of supercomputing 2020-03, Vol.76 (3), p.1754-1799
Main Authors: Shafqat, Sarah, Kishwer, Saira, Rasool, Raihan Ur, Qadir, Junaid, Amjad, Tehmina, Ahmad, Hafiz Farooq
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Cell phones
Compilers
Computer Science
Data analysis
Electronic devices
Electronic health records
Health care
Internet of Things
Interpreters
Mathematical analysis
Processor Architectures
Programming Languages
Systems analysis
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Summary:There is increased interest in deploying big data technology in the healthcare industry to manage massive collections of heterogeneous health datasets such as electronic health records and sensor data, which are increasing in volume and variety due to the commoditization of digital devices such as mobile phones and wireless sensors. The modern healthcare system requires an overhaul of traditional healthcare software/hardware paradigms, which are ill-equipped to cope with the volume and diversity of the modern health data and must be augmented with new “big data” computing and analysis capabilities. For researchers, there is an opportunity in healthcare data analytics to study this vast amount of data, find patterns and trends within data and provide a solution for improving healthcare, thereby reducing costs, democratizing health access, and saving valuable human lives. In this paper, we present a comprehensive survey of different big data analytics integrated healthcare systems and describe the various applicable healthcare data analytics algorithms, techniques, and tools that may be deployed in wireless, cloud, Internet of Things settings. Finally, the contribution is given in formation of a convergence point of all these platforms in form of SmartHealth that could result in contributing to unified standard learning healthcare system for future.
ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-017-2222-4