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The Novel Multi-Layered Approach to Enhance the Sorting Performance of Healthcare Analysis

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  • Ashish Seth

    (Inha University, South Korea)

  • Kirti Seth

    (Inha University in Tashkent, Uzbekistan)

  • Kirti Seth

    (Inha University in Tashkent, Uzbekistan)

  • Kirti Seth

    (Inha University in Tashkent, Uzbekistan)

Abstract

Emergence of big data in today’s world leads to new challenges for sorting strategies to analyze the data in a better way. For most of the analyzing technique, sorting is considered as an implicit attribute of the technique used. The availability of huge data has changed the way data is analyzed across industries. Healthcare is one of the notable areas where data analytics is making big changes. An efficient analysis has the potential to reduce costs of treatment and improve the quality of life in general. Healthcare industries are collecting massive amounts of data and look for the best strategies to use these numbers. This research proposes a novel non-comparison based approach to sort a large data that can further be utilized by any big data analytical technique for various analyses.

Suggested Citation

  • Ashish Seth & Kirti Seth & Kirti Seth & Kirti Seth, 2022. "The Novel Multi-Layered Approach to Enhance the Sorting Performance of Healthcare Analysis," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global, vol. 11(3), pages 1-14, July.
    • Handle: RePEc:igg:jrqeh0:v:11:y:2022:i:3:p:1-14
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJRQEH.289178
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    References listed on IDEAS

    as
    1. Ashish Seth & Kirti Seth, 2021. "Optimal Composition of Services for Intelligent Systems Using TOPSIS," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 11(3), pages 49-64, July.
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