Skip to main content

Adaptation and Medical Case-Based Reasoning Focusing on Endocrine Therapy Support

  • Conference paper
Book cover Artificial Intelligence in Medicine (AIME 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3581))

Included in the following conference series:

Abstract

So far, Case-Based Reasoning has not become as successful in medicine as in some other application domains. One, probably the main reason is the adaptation problem. In Case-Based Reasoning the adaptation task still is domain dependent und usually requires specific adaptation rules. Furthermore, in medicine adaptation is often more difficult than in other domains, because usually more and complex features have to be considered. We have developed some programs for endocrine therapy support, especially for hypothyroidism. In this paper, we do not present them in detail, but focus on adaptation. We do not only summarise experiences with adaptation in medicine, but we want to elaborate typical medical adaptation problems and hope to indicate possibilities how to solve them.

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. Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications 7(1), 39–59 (1994)

    Google Scholar 

  2. Stottler, R., et al.: Rapid retrieval algorithms for case-based reasoning. In: Proc. of 11th Int Joint Conference on Artificial Intelligence, pp. 233–237. Morgan Kaufmann Publishers, San Mateo (1989)

    Google Scholar 

  3. Broder, A.: Strategies for efficient incremental nearest neighbor search. Pattern Recognition 23, 171–178 (1990)

    Article  Google Scholar 

  4. Quinlan, J.: C4.5, Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993)

    Google Scholar 

  5. Bergmann, R., Wilke, W.: Towards a new formal model of transformational adaptation in case-based reasoning. In: Gierl, L., Lenz, M. (eds.) Proceedings of th German Workshop on CBR, pp. 43–52. University of Rostock (1998)

    Google Scholar 

  6. Fuchs, B., Mille, A.: A knowledge-level task model of adaptation in case-based reasoning. In: Althoff, K.-D., Bergmann, R., Branting, L.K., et al. (eds.) ICCBR 1999. LNCS (LNAI), vol. 1650, pp. 118–131. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  7. Gierl, L., Bull, M., Schmidt, R.: CBR in Medicine. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI), vol. 1400, pp. 273–297. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  8. Schmidt, R., Montani, S., Bellazzi, E., Portinale, L., Gierl, L.: Case-Based Reasoning for Medical Knowledge-based Systems. Int J Med Inform 64(2-3), 355–367 (2001)

    Article  Google Scholar 

  9. Nilsson, M., Sollenborn, M.: Advancements and trends in medical case-based Reasoning: An overview of systems and system developments. In: Proc of FLAIRS, pp. 178–183. AAAI Press, Menlo Park (2004)

    Google Scholar 

  10. Perner, P.: Why Case-Based Reasoning is Attractive for Image Interpretation. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS (LNAI), vol. 2080, pp. 27–43. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  11. Schmidt, R., et al.: Medical multiparametric time course prognoses applied to kidney function assessments. Int J Med Inform 53(2-3), 253–264 (1999)

    Article  Google Scholar 

  12. Dugas, M.: Clinical applications of Intranet-Technology. In: Dudeck, J., et al. (eds.) New Technologies in Hospital Information Systems, pp. 115–118. IOS Press, Amsterdam (1997)

    Google Scholar 

  13. Montani, S., et al.: Diabetic patient’s management expoiting Case-based Reasoning techniques. Computer Methods and Programs in Biomedicine 62, 205–218 (2000)

    Article  Google Scholar 

  14. Bichindaritz, I., et al.: Case-based reasoning in CARE-PARTNER: Gathering evidence for evidence-based medical practice. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 334–345. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  15. Koton, P.: Reasoning about evidence in causal explanations. In: Kolodner, J. (ed.) First Workshop on CBR, pp. 260–270. Morgan Kaufmann Publishers, San Mateo (1988)

    Google Scholar 

  16. Schmidt, R., Gierl, L.: Case-based Reasoning for Antibiotics Therapy Advice: An Investigation of Retrieval Algorithms and Prototypes. Artificial Intelligence in Medicine 23(2), 171–186 (2001)

    Article  Google Scholar 

  17. Gierl, L., Stengel-Rutkowski, S.: Integrating consultation and semi-automatic knowledge acquisition in a prototype-based architecture: Experiences with Dysmorphic Syndromes. Artificial Intelligence in Medicine 6, 29–49 (1994)

    Article  Google Scholar 

  18. Petot, G.J., Marling, C., Sterling, L.: An artificial intelligence system for computer-assisted menu planing. Journal of American Diet Assoc 98(9), 1009–1014 (1998)

    Article  Google Scholar 

  19. Wilke, W., Smyth, B., Cunningham, P.: Using Configuration Techniques for Adaptation. In: Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D., Wess, S. (eds.) Case-Based Reasoning Technology. LNCS (LNAI), vol. 1400, pp. 139–168. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  20. Jurisica, I., et al.: Case-based reasoning in IVF: prediction and knowledge mining. Artificial Intelligence in Medicine 12, 1–24 (1998)

    Article  Google Scholar 

  21. Schmidt, R., Gierl, L.: Prognostic Model for Early Warning of Threatening Influenza Waves. In: Minor, M., Staab, S. (eds.) Proc 1st German Workshop on Experience Management, Köllen, Bonn, pp. 39–46 (2002)

    Google Scholar 

  22. Bichindaritz, I.: From cases to classes: Focusing on abstraction in case-based reasoning. In: Burkhard, H.-D., Lenz, M. (eds.) Proc of 4th German Workshop on CBR, pp. 62–69. Humboldt University, Berlin (1996)

    Google Scholar 

  23. Turner, R.: Organizing and using schematic knowledge for medical diagnosis. In: Kolodner, J. (ed.) First Workshop on CBR, pp. 435–446. Morgan Kaufmann Publishers, San Mateo (1988)

    Google Scholar 

  24. Schmidt, R., Vorobieva, O., Gierl, L.: Adaptation problems in therapeutic case-based reasoning systems. In: Palade, V., Howlett, R.J., Jain, L. (eds.) KES 2003. LNCS, vol. 2773, pp. 992–999. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  25. Hampel, R.: Diagnostik und Therapie von Schilddrüsenfunktionsstörungen. UNI-MED Verlag, Bremen (2000)

    Google Scholar 

  26. DeGroot, L.J.: Thyroid Physiology and Hypothyroidsm. In: Besser, G.M., Turner, M. (eds.) Clinical endocrinilogy, ch. 15. Wolfe, London (1994)

    Google Scholar 

  27. Tversky, A.: Features of similarity. Psychological review 84, 327–352 (1977)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schmidt, R., Vorobieva, O. (2005). Adaptation and Medical Case-Based Reasoning Focusing on Endocrine Therapy Support. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_42

Download citation

  • DOI: https://doi.org/10.1007/11527770_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27831-3

  • Online ISBN: 978-3-540-31884-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics