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Case-Based Reasoning for Prognosis of Threatening Influenza Waves

  • Rainer Schmidt
  • Lothar Gierl
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2394)

Abstract

The goal of the TeCoMed project is to compute early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, and to send them to interested practitioners, pharmacists etc. in the German federal state of Mecklenburg-Western Pomerania. Usually, each winter one influenza wave can be observed in Germany. In some years they are nearly unnoticeable, while in other years doctors and pharmacists even run out of vaccine. Because of the irregular cyclic behaviour it is insufficient to determine average values based on former years and to give warnings as soon as such values are noticeably overstepped. So, we have developed a method that combines Temporal Abstraction with Case-based Reasoning. The idea is to search for former, similar cases and to make use of them for the decision whether early warning is appropriate or not.

Keywords

Early Warning Health Insurance Company Weekly Data German Federal State Temporal Abstraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Rainer Schmidt
    • 1
  • Lothar Gierl
    • 1
  1. 1.Institut für Medizinische Informatik und BiometrieUniversität RostockRostockGermany

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