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A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector

机译:系统审查医疗部门大数据的技术和来源

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The main objective of this paper is to present a review of existing researches in the literature, referring to Big Data sources and techniques in health sector and to identify which of these techniques are the most used in the prediction of chronic diseases. Academic databases and systems such as IEEE Xplore, Scopus, PubMed and Science Direct were searched, considering the date of publication from 2006 until the present time. Several search criteria were established as 'techniques' OR 'sources' AND 'Big Data' AND 'medicine' OR 'health', 'techniques' AND 'Big Data' AND 'chronic diseases', etc. Selecting the paper considered of interest regarding the description of the techniques and sources of Big Data in healthcare. It found a total of 110 articles on techniques and sources of Big Data on health from which only 32 have been identified as relevant work. Many of the articles show the platforms of Big Data, sources, databases used and identify the techniques most used in the prediction of chronic diseases. From the review of the analyzed research articles, it can be noticed that the sources and techniques of Big Data used in the health sector represent a relevant factor in terms of effectiveness, since it allows the application of predictive analysis techniques in tasks such as: identification of patients at risk of reentry or prevention of hospital or chronic diseases infections, obtaining predictive models of quality.
机译:本文的主要目的是介绍文献中存在的研究,指的是卫生部门的大数据来源和技术,并确定这些技术是在预测慢性疾病中最常用的技术。考虑到2006年直到现在的出版日期,搜索了IEEE Xplore,Scopus,Pubmed和Science等学术数据库和系统,如IEEE Xplore,Scopus,PubMed和Science Direct。几个搜索标准被建立为“技术”或“来源”和“大数据”和“医学”或“健康”,“技术”和“大数据”等,选择了关于对兴趣感兴趣的论文医疗保健中大数据的技术和来源的描述。它发现了110篇关于健康数据的技术和大数据来源的文章,只有32次被确定为相关工作。许多文章都显示了大数据,来源,使用的数据库的平台,并识别最多用于预测慢性疾病的技术。从审查分析的研究文章中,可以注意到,卫生部门中使用的大数据的来源和技术在有效性方面代表了相关因素,因为它允许在诸如:识别的任务中应用预测性分析技术患者患者患有再入或预防医院或慢性疾病感染,获得了质量的预测模型。

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