@article{A01a,
Author = {A. Schlaefer and K. Schroeter and L. Fritsche},
Title = {A Case-Based Approach for the Classification of Medical Time Series.},
Journal = {<em>J. Crespo, V. Maojo, F. Martin (Eds.): Medical Data Analysis</em>.},
Year = {(2001).},
Volume = {<strong>2199</strong>.},
Pages = {258-263},
Note = {Springer LNCS 2199},
Url = {http://link.springer.com/chapter/10.1007%2F3-540-45497-7_39},
Abstract = {An early and reliable detection of rejections is most important for the successful treatment of renal transplantation patients. A good indicator for the renal function of transplanted patients is the course over time of the parameter creatinine. Existing systems for the analysis of time series usually require frequent and equidistant measurements or a well defined medical theory. These requirements are not fulfilled in our application domain. In this paper we present a case-based approach to classify a creatinine course as critical or non-critical. The distance measure used to find similar cases is based on linear regression. Our results show that while having a good specificity, our sensitivity is significantly higher than that of physicians}
}

@COMMENT{Bibtex file generated on 2026-5-13 with typo3 si_bibtex plugin. Data from https://www.tuhh.de/mtec/publications/2012-2000 }