Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/18938

TitleInformation modeling for real-time decision support in intensive medicine
Author(s)Santos, Manuel
Portela, Filipe
Vilas-Boas, Marta
Machado, José Manuel
Abelha, António
Neves, José
Silva, Álvaro
Rua, Fernando
KeywordsReal-time data acquisition
Knowledge discovery in databases
Intensive care
INTCare
Intelligent decision support systems
Information models
Issue date2009
PublisherWorld Scientific and Engineering Academy and Society (WSEAS)
JournalWSEAS Transactions on Computers
Abstract(s)Daily, a great amount of data that is gathered in intensive care units, which makes intensive medicine a very attractive field for applying knowledge discovery in databases. Previously unknown knowledge can be extracted from that data in order to create prediction and decision models. The challenge is to perform those tasks in real-time, in order to assist the doctors in the decision making process. Furthermore, the models should be continuously assessed and optimized, if necessary, to maintain a certain accuracy. In this paper we propose an information architecture to support an adjustment to the INTCare system, an intelligent decision support system for intensive medicine. We focus on the automatization of data acquisition avoiding human intervention, describing its steps and some requirements.
TypeConference paper
URIhttp://hdl.handle.net/1822/18938
ISBN9789604740758
ISSN1109-2750.
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:DI/CCTC - Artigos (papers)

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