Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/67833

TítuloTowards of a real-time Big Data architecture to intensive care
Autor(es)Goncalves, Andre
Portela, Filipe
Santos, Manuel
Rua, Fernando
Palavras-chaveIntensive Medicine
Intensive Care Units
Real-time
Big Data
Architecture
Hadoop
Data2017
EditoraElsevier Science BV
RevistaProcedia Computer Science
Resumo(s)These days the exponential increase in the volume and variety of data stored by companies and organizations of various sectors of activity, has required to organizations the search for new solutions to improve their services and/or products, taking advantage of technological evolution. As a response to the inability of organizations to process large quantities and varieties of data, in the technological market, arise the Big Data. This emerging concept defined mainly by the volume, velocity and variety has evolved greatly in part by its ability to generate value for organizations in decision making. Currently, the health care sector is one of the five sectors of activity where the potential of Big Data growth most stands out. However, the way to go is still long and in fact there are few organizations, related to health care, that are taking advantage of the true potential of Big Data. The main target of this research is to produce a real-time Big Data architecture to the INTCare system, of the Centro Hospitalar do Porto, using the main open source big data solution, the Apache Hadoop. As a result of the first phase of this research we obtained a generic architecture who can be adopted by other Intensive Care Units.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/67833
DOI10.1016/j.procs.2017.08.294
ISSN1877-0509
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S1877050917317039
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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