Skip to main content

Case-Based Reasoning for Breast Cancer Treatment Decision Helping

  • Conference paper
  • First Online:
Advances in Case-Based Reasoning (EWCBR 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1898))

Included in the following conference series:

Abstract

This paper presents two applications for the breast cancer treatment decision helping. The first one is called Casimir/RBR and can be likened to a rule-based reasoning system. In some situations, the application of the rules of this system does not provide a satisfying treatment. Then, the application Casimir/CBR-which is not fully implementedcan be used. Casimir/CBR uses principles of case-based reasoning in order to suggest solutions by adapting the rules of Casimir/RBR. In this framework, the rules are considered as cases: they are adapted rather than used literally.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A. Aamodt and E. Plaza. Case-based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications, 7(1):39–59, 1994.

    Google Scholar 

  2. R. Bergmann and W. Wilke. Building and Refining Abstract Planning Cases by Change of Representation Language. Journal of Artificial Intelligence Research, 3:53–118, 1995.

    Google Scholar 

  3. G. Boussu. Apprentissage á partir d’échecs. Mémoire de DEA d’informatique, Université Henri Poincaré Nancy 1, 1998.

    Google Scholar 

  4. L. K. Branting and D. W. Aha. Stratified Case-Based Reasoning: Reusing Hierarchical Problem Solving Episodes. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI’95), Montréal, volume 1, pages 384–390, August 1995.

    Google Scholar 

  5. Béatrice Fuchs, Jean Lieber, Alain Mille, and Amedeo Napoli. Towards a Unified Theory of Adaptation in Case-Based Reasoning. In K.-D. Althoff, R. Bergmann, and L. K. Branting, (nt(editors)), Case-Based Reasoning Reasearch and Development— Third International Conference on Case-Based Reasoning (ICCBR-99), Lecture Notes in Artificial Intelligence 1650. Springer, Berlin, 1999.

    Google Scholar 

  6. K. J. Hammond. Explaining and Repairing Plans That Fail. Artificial Intelligence, 45:173–228, 1990.

    Article  Google Scholar 

  7. J. Lieber and A. Napoli. Using Classification in Case-Based Planning. In W. Wahlster, (nt(editor)), Proceedings of the 12th European Conference on Artificial Intelligence (ECAI’96), Budapest, Hungary, pages 132–136. John Wiley & Sons, Ltd., 1996.

    Google Scholar 

  8. J. Lieber and A. Napoli. Correct and Complete Retrieval for Case-Based Problem-Solving. In H. Prade, (nt(editor)), Proceedings of the 13th European Conference on Artificial Intelligence (ECAI-98), Brighton, United Kingdom, pages 68–72, 1998.

    Google Scholar 

  9. E. Melis, J. Lieber, and A. Napoli. Reformulation in Case-Based Reasoning. In B. Smyth and P. Cunningham, (nt(editors)), Fourth European Workshop on Case-Based Reasoning, EWCBR-98, Lecture Notes in Artificial Intelligence 1488, pages 172–183. Springer, 1998.

    Google Scholar 

  10. C. K. Riesbeck and R. C. Schank. Inside Case-Based Reasoning. Lawrence Erlbaum Associates, Inc., Hillsdale, New Jersey, 1989.

    Google Scholar 

  11. B. Séroussi, J. Bouaud, and É.-C. Antoine. Enhancing Clinical Practice Guideline Compliance by Involving Physicians in the Decision Process. In W. Horn, Y. Shahar, G. Lindberg, S. Andreassen, and J. Wyatt, (nt(editors)), Proceedings of the Joint European Conference on Artificial Intellingence in Medicine and Medical Decision Making (AIMDM-99), volume 1620 of LNAI, pages 76–85, Berlin, 1999. Springer.

    Google Scholar 

  12. B. Smyth and M. T. Keane. Using adaptation knowledge to retrieve and adapt design cases. Knowledge-Based Systems, 9(2):127–135, 1996.

    Article  Google Scholar 

  13. P. Vismara. Reconnaissance et représentation d’éléments structuraux pour la description d’objets complexes. Application á l’élaboration de stratégies de synthèse en chimie organique. Thèse de l’Université des Sciences et Techniques du Languedoc, Montpellier, 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lieber, J., Bresson, B. (2000). Case-Based Reasoning for Breast Cancer Treatment Decision Helping. In: Blanzieri, E., Portinale, L. (eds) Advances in Case-Based Reasoning. EWCBR 2000. Lecture Notes in Computer Science, vol 1898. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44527-7_16

Download citation

  • DOI: https://doi.org/10.1007/3-540-44527-7_16

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67933-2

  • Online ISBN: 978-3-540-44527-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics