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dc.contributor.authorFried, Roland
dc.contributor.authorGather, Ursula
dc.contributor.editorSchubert, Sigrid E.
dc.contributor.editorReusch, Bernd
dc.contributor.editorJesse, Norbert
dc.date.accessioned2019-11-28T09:31:23Z
dc.date.available2019-11-28T09:31:23Z
dc.date.issued2002
dc.identifier.isbn3-88579-348-2
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/30311
dc.description.abstractPhysiological time series measured in intensive care exhibit trends, level changes and periods of relative constancy. This signal is overlaid with a high level of noise and many measurement artifacts, and there are dependencies between the different items measured. We develop a method which allows a reliable denoising of the data and which can separate artifacts from relevant changes in the patients condition. For clinical online application the method has to be automatized and work in real time.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofInformatik bewegt: Informatik 2002 - 32. Jahrestagung der Gesellschaft für Informatik e.v. (GI)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-19
dc.subjectMedical data analysis
dc.subjectonline monitoring
dc.subjectlevel shifts
dc.subjectoutliers
dc.titleRobust preprocessing of time series with trendsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages793-798
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationDortmund
mci.conference.date30. September - 3. Oktober 2002


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