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https://hdl.handle.net/1822/67833
Título: | Towards of a real-time Big Data architecture to intensive care |
Autor(es): | Goncalves, Andre Portela, Filipe Santos, Manuel Rua, Fernando |
Palavras-chave: | Intensive Medicine Intensive Care Units Real-time Big Data Architecture Hadoop |
Data: | 2017 |
Editora: | Elsevier Science BV |
Revista: | Procedia 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. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/67833 |
DOI: | 10.1016/j.procs.2017.08.294 |
ISSN: | 1877-0509 |
Versão da editora: | https://www.sciencedirect.com/science/article/pii/S1877050917317039 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2017 - Towards of a Real-time Big Data Architecture to Intensive Care .pdf | 931,04 kB | Adobe PDF | Ver/Abrir |