Abstract
Few years ago, we have developed an early warning system concerning multiparametric kidney function courses. As methods we applied Temporal Abstraction and Case-based Reasoning. In our current project we apply very similar ideas. The goal of the TeCoMed project is to compute early warnings against forthcoming waves or even epidemics of infectious diseases in the German federal state of Mecklenburg-Western Pomerania. Furthermore, these warnings shall be sent to interested practitioners, pharmacists etc. We have developed a prognostic model for diseases that are characterised by cyclic, but irregular behaviour. So far, we have applied this model to influenza and bronchitis.
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Schmidt, R., Gierl, L. (2003). Prognosis of Approaching Infectious Diseases. In: Dojat, M., Keravnou, E.T., Barahona, P. (eds) Artificial Intelligence in Medicine. AIME 2003. Lecture Notes in Computer Science(), vol 2780. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39907-0_4
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DOI: https://doi.org/10.1007/978-3-540-39907-0_4
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