PowerShell-based novel framework for Big health data analysis
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ORIGINAL RESEARCH
PowerShell-based novel framework for Big health data analysis Wei Ren1 • Dong Wan2 • Huifeng Zhu3 • Fangfang Liu4 • Greg Mirt6 • Fan Xu5
Received: 23 April 2020 / Accepted: 6 November 2020 Ó Bharati Vidyapeeth’s Institute of Computer Applications and Management 2020
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
Wei Ren, Dong Wan and Huifeng Zhu contributed equally to this work. & Greg Mirt [email protected] & Fan Xu [email protected] 1
Department of Humanities and Information Management, Chengdu Medical College, Chengdu 610500, China
2
First Affiliated Hospital of Chongqing Medical University, Chongqing 410016, China
3
College of Pharmaceutical Science and Chinese Medicine, Southwest University, Chongqing 400715, China
4
Southwest Minzu University, Chengdu 610500, China
5
Department of Public Health, Chengdu Medical College, Chengdu 610500, China
6
Neuro Occupational Activity Centre Novo mesto, Ljubljana, Slovenia
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-bystep operation here to help readers grab a general idea of its mechanism. Keywords Big data Segment Breakdown PowerShell
1 Introduction Big data in health care includes but not limited to medical health record, treatment outcome and image-derived information [1, 2]. As these data increased significantly in size over time, it posts great challenges on machine learning. From the time of the introduction of big data, it has been used in numerous areas, ranging from commercial activities to public administration, from academic research to machine learning [3–7]. In 2019, Damini Dey et al. highlighted in their review that diagnostic support will be provided by automated image segmentation [8]. Nafea proposed an approach to handle big data issue to improve healthcare service and aid disease prevention work [9]. Ma et al. proposed an effective algorithm for segmenting real imagery and bioinformatic data. They also supported idea that segmentation (or clustering) is widely recognized as an important step in interpreting big data [10]. Likewise, Task
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