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Case-based reasoning and statistics for discovering and forecasting of epidemics

  • Hybrid and Cooperative Systems
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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1211))

Abstract

We describe the methodology of an early warning system which fulfills the following tasks. (1) discovering of health risks, (2) forecasting of the temporal and spatial spread of epidemics and (3) estimating of consequences of an epidemic w.r.t. the personnel load and costs of the public health service. For mastering this three tasks methods from artifical intelligence and statistics are applied.

supported by the DFN-Verein (German society for the national research net) and the AOK Mecklenburg-Vorpommern (General health insurance company)

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Elpida Keravnou Catherine Garbay Robert Baud Jeremy Wyatt

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© 1997 Springer-Verlag Berlin Heidelberg

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Bull, M., Kundt, G., Gierl, L. (1997). Case-based reasoning and statistics for discovering and forecasting of epidemics. In: Keravnou, E., Garbay, C., Baud, R., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIME 1997. Lecture Notes in Computer Science, vol 1211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029485

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  • DOI: https://doi.org/10.1007/BFb0029485

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62709-8

  • Online ISBN: 978-3-540-68448-0

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