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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 3/2020

03.02.2018

Big data analytics enhanced healthcare systems: a review

verfasst von: Sarah Shafqat, Saira Kishwer, Raihan Ur Rasool, Junaid Qadir, Tehmina Amjad, Hafiz Farooq Ahmad

Erschienen in: The Journal of Supercomputing | Ausgabe 3/2020

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Abstract

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.
Vorheriger Artikel An adaption scheduling based on dynamic weighted random forests for load demand forecasting
Nächster Artikel Emergent models, frameworks, and hardware technologies for Big data analytics

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Metadaten
Titel
Big data analytics enhanced healthcare systems: a review
verfasst von
Sarah Shafqat
Saira Kishwer
Raihan Ur Rasool
Junaid Qadir
Tehmina Amjad
Hafiz Farooq Ahmad
Publikationsdatum
03.02.2018
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 3/2020
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-017-2222-4

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