Graphical Models for Multivariate Time Series from Intensive Care Monitoring

dc.contributor.author	Fried, Roland	de
dc.contributor.author	Gather, Ursula	de
dc.contributor.author	Imhoff, Michael	de
dc.date.accessioned	2004-12-06T18:42:41Z
dc.date.available	2004-12-06T18:42:41Z
dc.date.issued	2000	de
dc.description.abstract	In critical care extremely high dimensional time series are generated by clinical information systems. This yields new perspectives of data recording and also causes a new challenge for statistical methodology. Recently graphical correlation models have been developed for analysing the partial associations between the components of multivariate time series. We apply this technique to the hemodynamic system of critically ill patients monitored in intensive care. We appraise the practical value of the procedure by reidentifying known associations between the variables. From separate analyses for different pathophysiological states we conclude that distinct clinical states can be characterised by distinct partial correlation structures.	en
dc.format.extent	371470 bytes
dc.format.extent	689830 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/5037
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-5385
dc.language.iso	en	de
dc.publisher	Universitätsbibliothek Dortmund	de
dc.subject.ddc	310	de
dc.title	Graphical Models for Multivariate Time Series from Intensive Care Monitoring	en
dc.type	Text	de
dc.type.publicationtype	report	en
dcterms.accessRights	open access

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