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A comparative evaluation of three approaches to the acquisition of medical knowledge

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Book cover AIME 91

Part of the book series: Lecture Notes in Medical Informatics ((LNMED,volume 44))

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Abstract

At present there are several different approaches to the problem of knowledge acquisition for Knowledge-Based Systems. This paper describes a comparative evaluation of three approaches, applied to the same medical domain: diagnosing chest pain. The first approach is what we call the ’compiled knowledge acquisition approach’, the second is ’machine induction’, the third ’knowledge structuring’. For each approach a version was designed that uses a set of cases diagnosed by experts as reference. The resulting knowledge bases were compared in terms of problem solving performance, the quality of the knowledge base and the effort spent on knowledge acquisition. Performance was also compared with human experts.

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References

  1. B. Porter R. Bareiss and C. Wier. Protos–an exemplar based learning apprentice. Int. J. Man-Machine Studies, 29: 549–561, 1988.

    Article  Google Scholar 

  2. J. A. Breuker and B. J. Wielinga. Model Driven Knowledge Acquisition. In P. Guida and G. Tasso, editors, Topics in the Design of Expert Systems, pages 265–296, Amsterdam, 1989. North Holland.

    Google Scholar 

  3. B.G. Buchanan and E.H. Shortliffe. Rulebased Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project. Addison Wesley, Reading, Massachusetts, 1984.

    Google Scholar 

  4. Clancey, 1983] W.J. Clancey. The epistemology of a rule based system –a framework for explanation. Artificial Intelligence,20:215251, 1983. Also: Stanford Heuristic Programming Project, Memo HPP-81–17, November 1981, also numbered STANCS-81–896.

    Google Scholar 

  5. D. A. Evans and V. L. Patel. Cognitive Science in Medicine. MIT Press, Cambridge, Massachusets, 1989.

    Google Scholar 

  6. A. Ginsberg. Refinement of Expert System Knowledge Bases: A Metalinguistic Frame Work for Heuristic Analysis. Pitman, 1988.

    Google Scholar 

  7. J. Hong, I. Mozetic, and R.S. Michalski. Aq15: incremental learning of attribute-based descriptions from expamples, the method and user’s guide. Technical report, Department of Computer Science, University of Illinois, Urbana-Champaign, 1986.

    Google Scholar 

  8. R.S. Michalski. A theory and methodology of inductive learning. In R.S. Michalski, J.G. Carbonell, and T.M. Mitchell, editors, Machine learning: an Artificial Intelligence Approach. Springer-Verlag, 1983.

    Google Scholar 

  9. R. Neches, W.R. Swartout, and J.D. Moore. Enhanced maintenance and explanation of expert systems through explicit models of their development. IEEE Trans. Softw. Eng., 11: 1337–1351, 1985.

    Article  Google Scholar 

  10. V. L. Patel, D. A. Evans, and D. R. Kaufman A cognitive framework for doctor-patient interaction. In D. A. Evans and V. L. Patel, editors, Cognitive Science in Medicine, pages 257–312. MIT Press, 1989.

    Google Scholar 

  11. J.R. Quinlan. Learning efficient classification, procedures and their application to chess end games. In R.S. Michalski, J.G. Carbonell, and T.M. Mitchell, editors, Machine learning: An Artificial Intelligence Approach, chapter 15. Tioga, Palo Alto, CA, 1983.

    Google Scholar 

  12. N. Shadbolt and B.J. Wielinga. Knowledge based knowledge acquisition: the next generation of support tools. In B. J. Wielinga, J. Boose, B. Gaines, G. Schreiber, and M.W. van Someren, editors, Current trends in knowledge acquisition, pages 313–338. IOS Press, 1990.

    Google Scholar 

  13. M. W. van Someren, L. L. Zheng, and W. Post. Cases, models or compiled knowledge? - a comparative analysis and proposed integration. In B. J. Wielinga, J. Boose, B. Gaines, G. Schreiber, and M.W. van Someren, editors, Current trends in knowledge acquisition, pages 339–355. IOS Press, 1990.

    Google Scholar 

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© 1991 Springer-Verlag Berlin Heidelberg

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Post, W., van Someren, M.W. (1991). A comparative evaluation of three approaches to the acquisition of medical knowledge. In: Stefanelli, M., Hasman, A., Fieschi, M., Talmon, J. (eds) AIME 91. Lecture Notes in Medical Informatics, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48650-0_21

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  • DOI: https://doi.org/10.1007/978-3-642-48650-0_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54144-8

  • Online ISBN: 978-3-642-48650-0

  • eBook Packages: Springer Book Archive

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