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AtherEx: An Expert System for Atherosclerosis Risk Assessment

  • Conference paper
Artificial Intelligence in Medicine (AIME 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3581))

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Abstract

A number of calculators that compute the risk of atherosclerosis has been developed and made available on the Internet. They all are based on computing weighted sum of risk factors. We propose instead to use more flexible expert systems to estimate the risk. The goal of the AtherEx expert system is to classify patients according to their atherosclerosis risk into four groups. This application is based on the Nest rule–based expert system shell. Knowledge for the AtherEx was obtained (using the machine learning algorithm KEX) from the data concerning a longitudial study of atherosclerosis risk factors and further refined by domain expert. AtherEx is available for consultations on web.

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References

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Author information

Authors and Affiliations

  1. University of Economic, Prague, Czech Republic

    Petr Berka & Vladimír Laš

  2. Institute of Computer Science, Academy of Sciences, Prague, Czech Republic

    Marie Tomečková

Authors
  1. Petr Berka
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  2. Vladimír Laš
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  3. Marie Tomečková
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Editor information

Editors and Affiliations

  1. Department of Information and Knowledge Engineering, Danube University Krems, Dr.-Karl-Dorrek-Str. 30, 3500, Krems, Austria

    Silvia Miksch

  2. Department of Computing Science, University of Aberdeen, AB24 3UE, Aberdeen, UK

    Jim Hunter

  3. Department of Computer Science, University of Cyprus, P.O.Box 20537, CY-1678, Nicosia, Cyprus

    Elpida T. Keravnou

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© 2005 Springer-Verlag Berlin Heidelberg

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Berka, P., Laš, V., Tomečková, M. (2005). AtherEx: An Expert System for Atherosclerosis Risk Assessment. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_11

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  • DOI: https://doi.org/10.1007/11527770_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27831-3

  • Online ISBN: 978-3-540-31884-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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