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| text     = This is sublevel13 of my sandbox, where I play with features and test MediaWiki code. If you wish to leave a comment for me, please see [[User_talk:Shawndouglas|my discussion page]] instead.<p></p>
|title_full  = DataCare: Big data analytics solution for intelligent healthcare management
|journal     = ''International Journal of Interactive Multimedia and Artificial Intelligence''
|authors      = Baldominos, Alejandro; de Rada, Fernando; Saez, Yago
|affiliations =  Universidad Carlos III de Madrid, Camilo José Cela University
|contact      = Email: abaldomi at inf dot uc3m dot es
|editors      =
|pub_year    = 2018
|vol_iss      = '''4'''(7)
|pages        = 13–20
|doi          = [http://10.9781/ijimai.2017.03.002 10.9781/ijimai.2017.03.002]
|issn        = 1989-1660
|license      = [https://creativecommons.org/licenses/by/3.0/ Creative Commons Attribution 3.0 Unported]
|website      = [http://www.ijimai.org/journal/node/1621 http://www.ijimai.org/journal/node/1621]
|download    = [http://www.ijimai.org/journal/sites/default/files/files/2017/03/ijimai_4_7_2_pdf_16566.pdf http://www.ijimai.org/journal/sites/default/files/files/2017/03/ijimai_4_7_2_pdf_16566.pdf] (PDF)
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==Abstract==
This paper presents DataCare, a solution for intelligent healthcare management. This product is able not only to retrieve and aggregate data from different key performance indicators in healthcare centers, but also to estimate future values for these key performance indicators and, as a result, fire early alerts when undesirable values are about to occur or provide recommendations to improve the quality of service. DataCare’s core processes are built over a free and open-source cross-platform document-oriented database (MongoDB), and Apache Spark, an open-source cluster computing framework. This architecture ensures high scalability capable of processing very high data volumes coming at rapid speeds from a large set of sources. This article describes the architecture designed for this project and the results obtained after conducting a pilot in a healthcare center. Useful conclusions have been drawn regarding how key performance indicators change based on different situations, and how they affect patients’ satisfaction.
'''Keywords''': Architecture, artificial intelligence, big data, healthcare, management
==References==
{{Reflist|colwidth=30em}}
==Notes==
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added. The original article lists references alphabetically, but this version — by design — lists them in order of appearance.


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[[Category:LIMSwiki journal articles (added in 2018)‎]]
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[[Category:LIMSwiki journal articles on big data‎‎]]
[[Category:LIMSwiki journal articles on health informatics‎‎]]

Latest revision as of 20:47, 1 December 2023

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