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Knowledge-based systems for lymph node pathology: A comparison of two approaches

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Artificial Intelligence in Medicine (AIME 1995)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 934))

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Abstract

A formal evaluation was performed between two knowledge-based systems for lymph node pathology: 1) Intellipath, Kiel edition, a Bayesian system; and, 2) “Professor Amadeus”, which uses categorical reasoning and defined diagnostic patterns. The evaluation, involving three pathologists, was based on 57 lymph node biopsies. Intellipath demonstrated satisfactory performance, with from 63.2% to 71.9% correct answers, depending on the experience level of the pathologist. “Professor Amadeus” achieved better results, with accuracy rates ranging from 93% to 96.5%. In this study, the better performance of “Professor Amadeus” could be attributed to a more effective multiparameter approach, fewer errors in the knowledge base, and better handling of input parameters.

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Authors and Affiliations

  1. Pathology Institute, University of Cologne, Germany

    D. T. Nguyen, I. A. Park, P. Cherubino, P. B. Tamino & L. W. Diamond

Authors
  1. D. T. Nguyen
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  2. I. A. Park
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  3. P. Cherubino
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  4. P. B. Tamino
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  5. L. W. Diamond
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Editor information

Pedro Barahona Mario Stefanelli Jeremy Wyatt

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© 1995 Springer-Verlag Berlin Heidelberg

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Nguyen, D.T., Park, I.A., Cherubino, P., Tamino, P.B., Diamond, L.W. (1995). Knowledge-based systems for lymph node pathology: A comparison of two approaches. In: Barahona, P., Stefanelli, M., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIME 1995. Lecture Notes in Computer Science, vol 934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60025-6_142

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  • DOI: https://doi.org/10.1007/3-540-60025-6_142

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60025-1

  • Online ISBN: 978-3-540-49407-2

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