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.
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Schlaefer, A., Schröter, K., Fritsche, L. (2001). A Case-Based Approach for the Classification of Medical Time Series. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_39
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DOI: https://doi.org/10.1007/3-540-45497-7_39
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