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PowerShell-based novel framework for Big health data analysis

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Abstract

An obvious feature of the big data is overload. When we are held up in the Lake of big data, it is necessary to filter the most meaningful information [Khan et al. (ICCWAMTIP 2018:232–236, 2018), (Int J Inf Technol 12(2):409–417, 2020)]. The key element is segmentation, which involves the breakdown of the dataset into smaller ones. MIMIC-III (Medical Information Mart for Intensive Care III), an open critical care database, comprises data flow that encompasses patient information during whole hospital length of stay, i.e., from the beginning of hospital admission to patients’ discharge from the hospital. As MIMIC III stores a large volume of shared data, selecting useful data using traditional data mining approach to tailor academic research would be time consuming and resource demanding. Herein, we introduced a robust Windows build-in tool known as PowerShell, which is used to segment the big data into a practical dataset. Since the PowerShell script is open on the platform to demonstrate its use for further public research, we would present the step-by-step operation here to help readers grab a general idea of its mechanism.

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Acknowledgements

We thank the Chengdu Medical College for providing a robust and valuable big data platform to perform the big data analysis.

Funding

This work was supported by the Chengdu Medical College Foundation (CYZ-18-33, CYZ19-33), Chengdu Science and Technology Bureau focuses on research and development support plan (2019-YF09-00097-SN), the popular scientific research project of Sichuan Health Commission (20PJ171), and Sichuan undergraduate innovation and startup program funding support (S201913705080, S201913705130, S201913705059, S202013705070, S202013705075, S202013705108), Yun Nan Education Program (SYSX202036).

Author information

Author notes

  1. Wei Ren, Dong Wan and Huifeng Zhu contributed equally to this work.

Authors and Affiliations

  1. Department of Humanities and Information Management, Chengdu Medical College, Chengdu, 610500, China

    Wei Ren

  2. First Affiliated Hospital of Chongqing Medical University, Chongqing, 410016, China

    Dong Wan

  3. College of Pharmaceutical Science and Chinese Medicine, Southwest University, Chongqing, 400715, China

    Huifeng Zhu

  4. Southwest Minzu University, Chengdu, 610500, China

    Fangfang Liu

  5. Department of Public Health, Chengdu Medical College, Chengdu, 610500, China

    Fan Xu

  6. Neuro Occupational Activity Centre Novo mesto, Ljubljana, Slovenia

    Greg Mirt

Authors
  1. Wei Ren
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  2. Dong Wan
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  3. Huifeng Zhu
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  4. Fangfang Liu
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  5. Greg Mirt
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  6. Fan Xu
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Contributions

FX and WR drafted the general outline; GM proofread and ensured the general language quality; DW, HFZ performed the PowerShell script drafts and tests, FFL drawn the figures.

Corresponding authors

Correspondence to Greg Mirt or Fan Xu.

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The authors declare that they have no conflict of interest.

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Ren, W., Wan, D., Zhu, H. et al. PowerShell-based novel framework for Big health data analysis. Int. j. inf. tecnol. 13, 287–290 (2021). https://doi.org/10.1007/s41870-020-00559-w

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  • DOI: https://doi.org/10.1007/s41870-020-00559-w

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