Analysis of High Dimensional Data from Intensive Care Medicine
| dc.contributor.author | Bauer, Marcus | de |
| dc.contributor.author | Gather, Ursula | de |
| dc.contributor.author | Imhoff, Michael | de |
| dc.date.accessioned | 2004-12-06T18:38:34Z | |
| dc.date.available | 2004-12-06T18:38:34Z | |
| dc.date.issued | 1998 | de |
| dc.description.abstract | As high dimensional data occur as a rule rather than an exception in critical care today, it is of utmost importance to improve acquisition, storage, modelling, and analysis of medical data, which appears feasable only with the help of bedside computers. The use of clinical information systems offers new perspectives of data recording and also causes a new challenge for statistical methodology. A graphical approach for analysing patterns in statistical time series from online monitoring systems in intensive care is proposed here as an example of a simple univariate method, which contains the possibility of a multivariate extension and which can be combined with procedures for dimension reduction. | en |
| dc.format.extent | 208799 bytes | |
| dc.format.extent | 608981 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.format.mimetype | application/postscript | |
| dc.identifier.uri | http://hdl.handle.net/2003/4855 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-5304 | |
| dc.language.iso | en | de |
| dc.publisher | Universitätsbibliothek Dortmund | de |
| dc.subject | clinical information systems | en |
| dc.subject | decision support | en |
| dc.subject | high dimensional time series | en |
| dc.subject | online monitoring | en |
| dc.subject | phase space reconstruction | en |
| dc.subject.ddc | 310 | de |
| dc.title | Analysis of High Dimensional Data from Intensive Care Medicine | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | en |
| dcterms.accessRights | open access |