Review of big data tools for healthcare system with case study on patient database storage methodology

Purva Grover, R. Johari
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引用次数: 4

Abstract

Over the years with automation more and more systems deployed in multiple industries are generating huge amount of data. In fact IT Industry itself has witnessed phenomenal growth of data in the recent years. The data generated in the last 5 years is much more then the data generated cumulatively by all the industries put together in the past 20 years. In the current work we focus on the ways and means to handle the data generated by PHIS(Personal Healthcare Information System). The big question which we have addressed in this paper is selection of the appropriate tool (Relational MySQL database or NoSQL MongoDB database) to store the patient data, its archival and storage, steps to mine it and concluded the work by depicting the comparative analysis in terms of space and time.
回顾医疗保健系统的大数据工具,并对患者数据库存储方法进行案例研究
多年来,随着自动化的发展,越来越多的系统部署在多个行业,产生了大量的数据。事实上,近年来IT行业本身也见证了数据的惊人增长。过去5年产生的数据比过去20年所有行业产生的数据总和还要多。在目前的工作中,我们的重点是处理个人卫生信息系统(PHIS)产生的数据的方法和手段。本文解决的主要问题是选择合适的工具(关系型MySQL数据库或NoSQL MongoDB数据库)来存储患者数据,其归档和存储,挖掘的步骤,并通过描述空间和时间的比较分析来结束工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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