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Acquisition and Representation of Causal and Temporal Knowledge in Medical Domains

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2774))

Abstract

In medical domains, a detailed model of diseases is necessary in order to provide useful explanations about the patient evolution. There are domains, for example Intensive Care Units (ICU), in which the temporal dimension plays an essential role in describing patient evolution over time. The inclusion of the temporal dimension in describing the diseases causal relations increases the problems associated to the so-called knowledge acquisition (KA) bottleneck. A KA tool is presented in this work to overcome these difficulties. This tool is built over the causal and temporal model ontology and the domain ontology, providing graphical wizards to guide the user through the KA process and to specify ontology mappings. Finally, the resulting knowledge base (KB) is physically implemented in Extensible Markup Language (XML) allowing an automatic diffusion of the KB throughout Internet.

This work is supported by the Spanish MCYT under the project “Information Systems and Intelligent Agents in ICU”,p roject number TIC2000-0873-C02-02.

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© 2003 Springer-Verlag Berlin Heidelberg

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Palma, J., Llamas, B., González, A., Menárguez, M. (2003). Acquisition and Representation of Causal and Temporal Knowledge in Medical Domains. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_174

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  • DOI: https://doi.org/10.1007/978-3-540-45226-3_174

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40804-8

  • Online ISBN: 978-3-540-45226-3

  • eBook Packages: Springer Book Archive

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