A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector
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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.
KeywordsBig data Chronic diseases Data mining Health sector Sources Techniques
This research has been partially supported by the European Commission and the Ministry of Industry, Energy and Tourism under the project AAL-20125036 named “WetakeCare: ICT- based Solution for (Self-) Management of Daily Living”, by National Funding from the FCT – Fundação para a Ciência e a Tecnologia through the UID/EEA/500008/2013 Project, by the Government of the Russian Federation, Grant 074-U01, and by Finep, with resources from Funttel, Grant No. 01.14.0231.00, under the Centro de Referência em Radiocomunicações - CRR project of the Instituto Nacional de Telecomunicações (Inatel), Brazil.
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they have no competing interests.
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