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Big Data Classification and Internet of Things in Healthcare

Author

Listed:
  • Amine Rghioui

    (Research Team in Smart Communications-ERSC–Research Centre E3S, EMI, Mohamed V University, Rabat, Morocco)

  • Jaime Lloret

    (Integrated Management Coastal Research Institute, Universitat Politecnica de Valencia, 46370 Valencia, Spain)

  • Abedlmajid Oumnad

    (Research Team in Smart Communications-ERSC–Research Centre E3S, EMI, Mohamed V University, Rabat, Morocco)

Abstract

Every single day, a massive amount of data is generated by different medical data sources. Processing this wealth of data is indeed a daunting task, and it forces us to adopt smart and scalable computational strategies, including machine intelligence, big data analytics, and data classification. The authors can use the Big Data analysis for effective decision making in healthcare domain using the existing machine learning algorithms with some modification to it. The fundamental purpose of this article is to summarize the role of Big Data analysis in healthcare, and to provide a comprehensive analysis of the various techniques involved in mining big data. This article provides an overview of Big Data, applicability of it in healthcare, some of the work in progress and a future works. Therefore, in this article, the use of machine learning techniques is proposed for real-time diabetic patient data analysis from IoT devices and gateways.

Suggested Citation

  • Amine Rghioui & Jaime Lloret & Abedlmajid Oumnad, 2020. "Big Data Classification and Internet of Things in Healthcare," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 11(2), pages 20-37, April.
    • Handle: RePEc:igg:jehmc0:v:11:y:2020:i:2:p:20-37
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