Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/15367

TitleEnabling real-time intelligent decision support in intensive care
Author(s)Portela, Filipe
Santos, Manuel Filipe
Gago, Pedro
Silva, Álvaro
Rua, Fernando
Abelha, António
Machado, José Manuel
Neves, José
KeywordsReal-Time
Intelligent decision support
Data engineering
Data mining
Intensive medicine
Agents
KDD
Issue dateOct-2011
PublisherEUROSIS-ETI
Abstract(s)Medical devices in ICU allow for both continuous monitoring of patients and data collection. Nevertheless, the amount of data to be considered is such that it is difficult for doctors to extract all the useful knowledge. In order to help uncover some of that knowledge we have built an IDSS based in the agent's paradigm and using data mining techniques to build prediction models. With the intention of collecting as much data as possible the data acquisition process was automated. Furthermore, given the paramount importance of data quality for data mining a data quality agent responsible for detecting the errors in the data was devised. Indeed, data acquisition in the ICU is error prone as, for instance, sensors may be displaced as patients move. The aim of this paper is to present the overall KDD process implemented, presenting in detail the data transformations that were done and the benefits achieved.
TypeConference paper
URIhttp://hdl.handle.net/1822/15367
ISBN9789077381663
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:DI/CCTC - Artigos (papers)
DSI - Engenharia e Gestão de Sistemas de Informação

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