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Internet-Based Decision-Support Server for Acute Abdominal Pain

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Artificial Intelligence in Medicine (AIMDM 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1620))

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Abstract

The paper describes conception and prototypical design of a decision-support server for acute abdominal pain. A user survey was initiated in three surgical departments to assess the user requirements concerning formal decision-aids. The results of this survey are presented. For scoring systems a work-up to separate terminological information from structure is described. The terminology is separately stored in a data dictionary and the structure in the knowledge base. This procedure enables a reuse of terminology for documentation and decision-support. The whole system covers a decision-support server written in C++ with underlying data dictionary and knowledge base, a documentation module written in Java and a Corba middleware (ORBacus 3.1) that establishes a connection via internet.

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References

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Authors and Affiliations

  1. Theoretical Surgery Unit, Dept. of General and Trauma Surgery, Heinrich-Heine University Düsseldorf, Germany

    H. P. Eich & C. Ohmann

Authors
  1. H. P. Eich
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  2. C. Ohmann
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Editor information

Editors and Affiliations

  1. Austrian Research Institute for Artificial Intelligence, Schottengasse 3, A-1010, Vienna, Austria

    Werner Horn

  2. Department of Medicine and Computer Science, Stanford University, 251 Campus Drive, Stanford, CA, 94305-5479, USA

    Yuval Shahar

  3. Department of Medicine Karolinska Institutet, Huddinge University Hospital, Sweden

    Greger Lindberg

  4. Department of Medical Informatics and Image Analysis, Aalborg University, Fredrik Bajers Vej 7D, DK-9000, Aalborg, Denmark

    Steen Andreassen

  5. School of Public Policy, University College London, 29/30 Tavistock Square, London, WC1H 9EZ, UK

    Jeremy Wyatt

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© 1999 Springer-Verlag Berlin Heidelberg

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Eich, H.P., Ohmann, C. (1999). Internet-Based Decision-Support Server for Acute Abdominal Pain. In: Horn, W., Shahar, Y., Lindberg, G., Andreassen, S., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIMDM 1999. Lecture Notes in Computer Science(), vol 1620. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48720-4_9

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  • DOI: https://doi.org/10.1007/3-540-48720-4_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66162-7

  • Online ISBN: 978-3-540-48720-3

  • eBook Packages: Springer Book Archive

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