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Real World—Big Data Analytics in Healthcare

Author

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  • Daniele Piovani

    (Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20090 Milan, Italy
    IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy)

  • Stefanos Bonovas

    (Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20090 Milan, Italy
    IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy)

Abstract

The term Big Data is used to describe extremely large datasets that are complex, multi-dimensional, unstructured, and heterogeneous and that are accumulating rapidly and may be analyzed with appropriate informatic and statistical methodologies to reveal patterns, trends, and associations [...]

Suggested Citation

  • Daniele Piovani & Stefanos Bonovas, 2022. "Real World—Big Data Analytics in Healthcare," IJERPH, MDPI, vol. 19(18), pages 1-3, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11677-:d:916852
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    References listed on IDEAS

    as
    1. Cox, D.R. & Kartsonaki, Christiana & Keogh, Ruth H., 2018. "Big data: Some statistical issues," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 111-115.
    2. Chien-Lung Chan & Chi-Chang Chang, 2020. "Big Data, Decision Models, and Public Health," IJERPH, MDPI, vol. 17(18), pages 1-7, September.
    3. Kurt Benke & Geza Benke, 2018. "Artificial Intelligence and Big Data in Public Health," IJERPH, MDPI, vol. 15(12), pages 1-9, December.
    4. Galetsi, P. & Katsaliaki, K. & Kumar, S., 2019. "Values, challenges and future directions of big data analytics in healthcare: A systematic review," Social Science & Medicine, Elsevier, vol. 241(C).
    Full references (including those not matched with items on IDEAS)

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