Statistical Methods in Intensive Care Online Monitoring

dc.contributor.author	Bauer, Marcus	de
dc.contributor.author	Fried, Roland	de
dc.contributor.author	Gather, Ursula	de
dc.contributor.author	Imhoff, Michael	de
dc.date.accessioned	2004-12-06T18:42:43Z
dc.date.available	2004-12-06T18:42:43Z
dc.date.issued	2000	de
dc.description.abstract	Intelligent alarm systems are needed for adequate bedside decision support in critical care. Clinical information systems acquire physiological variables online in short time intervals. To identify complications as well as therapeutic effects procedures for rapid classiffication of the current state of the patient have to be developed. Detection of characteristic patterns in the data can be accomplished by statistical time series analysis. In view of the high dimension of the data statistical methods for dimension reduction should be used in advance. We discuss the potential of statistical techniques for online monitoring.	en
dc.format.extent	262133 bytes
dc.format.extent	490816 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/5038
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-15129
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject.ddc	310	de
dc.title	Statistical Methods in Intensive Care Online Monitoring	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access
eldorado.dnb.deposit	true

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