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Conversational Case-Based Reasoning in Medical Classification and Diagnosis

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Artificial Intelligence in Medicine (AIME 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5651))

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Abstract

In case-based reasoning (CBR) approaches to classification and diagnosis, a description of the problem to be solved is often assumed to be available in advance. Conversational CBR (CCBR) is a more interactive approach in which the system is expected to play an active role in the selection of relevant tests to help minimize the number of problem features that the user needs to provide. We present a new algorithm for CCBR called iNN(k) and demonstrate its ability to achieve high levels of accuracy on a selection of datasets related to medicine and health care, while often requiring the user to provide only a small subset of the problem features required by a standard k-NN classifier. Another important benefit of iNN(k) is a goal-driven approach to feature selection that enables a CCBR system to explain the relevance of any question it asks the user in terms of its current goal.

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Author information

Authors and Affiliations

  1. School of Computing and Information Engineering, University of Ulster Coleraine, BT52 1SA, Northern Ireland, United Kingdom

    David McSherry

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  1. David McSherry
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Editor information

Editors and Affiliations

  1. University of Verona, Department of Computer Science, Ca’ Vignal 2, strada le Grazie 15, 37134, Verona, Italy

    Carlo Combi

  2. Department of Information Systems Engineering, Ben Gurion University of the Negev, P.O. Box 653, 84105, Beer-Sheva, Israel

    Yuval Shahar

  3. Department of Medical Informatics, University of Amsterdam, Academic Medical Center, Meibergdreef 15, 1105, Amsterdam, AZ, The Netherlands

    Ameen Abu-Hanna

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McSherry, D. (2009). Conversational Case-Based Reasoning in Medical Classification and Diagnosis. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds) Artificial Intelligence in Medicine. AIME 2009. Lecture Notes in Computer Science(), vol 5651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02976-9_16

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  • DOI: https://doi.org/10.1007/978-3-642-02976-9_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02975-2

  • Online ISBN: 978-3-642-02976-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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