Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications
Rainer Schmidt2 and Lothar Gierl2
| (2) |
Institut für Medizinische Informatik und Biometrie, Universität Rostock, D-18055 Rostock, Germany |
Abstract
We have developed a method for analysis and prognosis of multiparametric kidney function courses. The method combines two
abstraction steps (state abstraction and temporal abstraction) with Case-based Reasoning. Recently we have started to apply
the same method in the domain of Geomedicine, namely for the prognosis of the temporal spread of diseases, mainly of influenza,
where just one of the two abstraction steps is necessary, that is the temporal one. In this paper, we present the application
of our method in the kidney function domain, show how we are going to apply the same ideas for the prognosis of the spread
of diseases, and summarise the main principles of the method.
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