Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/21717

TitleA pervasive approach to a real-time intelligent decision support system in intensive medicine
Author(s)Portela, Filipe
Santos, Manuel Filipe
Vilas-Boas, Marta
KeywordsReal-time
Pervasive
Remotly access
Knowledge discovery in databases (KDD)
Intensive care
INTCare
Intelligent decision support systems (IDSS)
Intelligent decision support systems
Knowledge discovery in databases
Remotely access
Issue date2013
PublisherSpringer
JournalCommunications in Computer and Information Science
Abstract(s)The decision on the most appropriate procedure to provide to the patients the best healthcare possible is a critical and complex task in Intensive Care Units (ICU). Clinical Decision Support Systems (CDSS) should deal with huge amounts of data and online monitoring, analyzing numerous parameters and providing outputs in a short real-time. Although the advances attained in this area of knowledge new challenges should be taken into account in future CDSS developments, principally in ICUs environments. The next generation of CDSS will be pervasive and ubiquitous providing the doctors with the appropriate services and information in order to support decisions regardless the time or the local where they are. Consequently new requirements arise namely the privacy of data and the security in data access. This paper will present a pervasive perspective of the decision making process in the context of INTCare system, an intelligent decision support system for intensive medicine. Three scenarios are explored using data mining models continuously assessed and optimized. Some preliminary results are depicted and discussed.
TypeConference paper
URIhttp://hdl.handle.net/1822/21717
ISBN9783642297632
DOI10.1007/978-3-642-29764-9-25
ISSN1865-0929
Peer-Reviewedyes
AccessOpen access
Appears in Collections:DSI - Engenharia e Gestão de Sistemas de Informação

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