Skip to main content
SpringerLink
Log in

Exploring new roles for case-based reasoning in heterogeneous AI systems for medical decision support

  • Published:
Applied Intelligence Aims and scope Submit manuscript

Abstract

Background Supporting medical decision making is a complex task, that offers challenging research issues to Artificial Intelligence (AI) scientists. The Case-based Reasoning (CBR) methodology has been proposed as a possible means for supporting decision making in this domain since the 1980s. Nevertheless, despite the variety of efforts produced by the CBR research community, and the number of issues properly handled by means of this methodology, the success of CBR systems in medicine is somehow limited, and almost no research product has been fully tested and commercialized; one of the main reasons for this may be found in the nature of the problem domain, which is extremely complex and multi-faceted.

Materials and methods In this environment, we propose to design a modular architecture, in which several AI methodologies cooperate, to provide decision support. In the resulting context CBR, originally conceived as a well suited reasoning paradigm for medical applications, can extend its original roles, and cover a set of additional tasks.

Results and conclusions As an example, in the paper we will show how CBR can be exploited for configuring the parameters relied upon by other (reasoning) modules. Other possible ways of deploying CBR in this domain will be the object of our future investigations, and, in our opinion, a possible research direction for people working on CBR in the health sciences.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ledley R, Lusted L (1959) Reasoning foundations in medical diagnosis. Science 130:9–21

    Article  Google Scholar 

  2. Warner H, Toronto A, Veasy L (1964) Experience with Bayes’ theorem for computer diagnosis of congenital heart disease. Ann New York Acad Sci 115:2–16

    Google Scholar 

  3. Kolodner JL (1993) Case-based reasoning. Kaufmann, San Mateo

    Google Scholar 

  4. Aamodt A, Plaza E (1994) Case-based reasoning: foundational issues, methodological variations and systems approaches. AI Commun 7:39–59

    Google Scholar 

  5. Kolodner JL, Kolodner RM (1987) Using experience in clinical problem solving:introduction and framework. IEEE Trans Syst Man Cybern 17:420–431

    Article  Google Scholar 

  6. Stefanelli M (2001) The socio-organizational age of artificial intelligence in medicine. Artif Intell Med 23(1):25–47

    Article  Google Scholar 

  7. VanderSpek R, Spijkervet A (1997) Knowledge management: dealing intelligently with knowledge. In: Liebowitz J, Wilcox LC (eds) Knowledge management and its integrative elements. CRC, Boca Raton

    Google Scholar 

  8. Bichindaritz I, Marling C (2006) Case-based reasoning in the health sciences: what’s next? Artif Intell Med 36:127–135

    Article  Google Scholar 

  9. Montani S, Portinale L (2006) Accounting for the temporal dimension in case-based retrieval: a framework for medical applications. Comput Intell 22:208–223

    Article  MathSciNet  Google Scholar 

  10. Nilsson M, Funk P, Olsson E, vonScheele B, Xiong N (2006) Clinical decision-support for diagnosing stress-related disorders by applying psychophysiological medical knowledge to an instance-based learning system. Artif Intell Med 36:159–176

    Article  Google Scholar 

  11. ElBalaa Z, Strauss A, Uziel P, Maximini K, Traphoner R (2003) Fm-ultranet: a decision support system using case-based reasoning applied to ultrasonography. In: Proceedings of the case-based reasoning in the health sciences workshop, international conference on case based reasoning (ICCBR), Trondheim, pp 37–44

  12. Perner P, Janichen S, Perner H (2006) Case-based object recognition for airborne fungi recognition. Artif Intell Med 36:137–157

    Article  Google Scholar 

  13. Wu D, Weber R, Abramson FC (2004) A case-based framework for leveraging nutrigenomics knowledge and personalized nutrition counseling. In: Proceedings of the case-based reasoning in the health sciences workshop, European conference on case based reasoning (ECCBR), Madrid, pp 73–82

  14. Leake DB (1995) Combining rules and cases to learn case adaptation. In: Proceedings of the 17th international conference of cognitive science society, Pittsburgh

  15. Nilsson M, Sollenborn M (2004) Advancements and trends in medical case-based reasoning: an overview of systems and system development. In: Barr V, Markov Z (eds) Proceedings of the 17th international Florida artificial intelligence research society conference–special track on case-based reasoning. AAAI, Menlo Park, pp 9–18

    Google Scholar 

  16. Gierl L, Bull M, Schmidt R (1998) Cbr in medicine. In: Lenz M, Bartsch-Sporl B, Burkhard HD, Wess S (eds) Case-based reasoning technology: from foundations to applications. Springer, Berlin, pp 273–297

    Chapter  Google Scholar 

  17. Jang Y (1993) HYDI: a hybrid system with feedback for diagnosing multiple disorders. PhD thesis (TR-576), Computer Science, Massachusetts Institute of Technology, MA

  18. Hunter L (1989) Knowledge acquisition planning: gaining expertise through experience. PhD thesis (DCS-TR-678), Computer Science, Massachusetts Institute of Technology, MA

  19. Kahn CE, Anderson GM (1994) Case-based reasoning and imaging procedure selection. Invest Radiol 29:643–647

    Article  Google Scholar 

  20. Berger J (1989) Roentgen: a case-based approach to radiation therapy planning. In: Proceedings of the workshop on case-based reasoning. Kaufman, San Mateo, pp 218–223

    Google Scholar 

  21. Schmidt R, Pollwein B, Gierl L (1999) Case-based reasoning for antibiotics therapy advice. In: Althoff KD, Bergmann R, Branting LK (eds) Proceedings of the third international conference on case-based reasoning. Springer, Berlin, pp 550–559

    Google Scholar 

  22. Bichindaritz I, Marling C (2004) In: Second workshop on case based reasoning in the health sciences, ECCBR 2004. Technical Report 142-04, Departamento de Sistemas Informaticos y Programacion, Univesidad Complutense de Madrid, Madrid

  23. Bichindaritz I, Marling C (2005) In: Third workshop on case based reasoning in the health sciences, ICCBR 2005. DePaul University, Chicago

    Google Scholar 

  24. Shahar Y (1997) A framework for knowledge-based temporal abstractions. Artif Intell 90:79–133

    Article  MATH  Google Scholar 

  25. Schmidt R, Gierl L (2001) Temporal abstractions and case-based reasoning for medical course data. Two prognostic applications. In: Perner P (ed) Proceedings of the machine learning and data mining in pattern recognition: second international workshop. Lecture notes in computer science, vol 2123. Springer, Berlin, pp 23–34

    Chapter  Google Scholar 

  26. Montani S, Portinale L, Leonardi G, Bellazzi R, Bellazzi R (2006) Case-based retrieval to support the treatment of end stage renal failure patients. Artif Intell Med 37:31–42

    Article  Google Scholar 

  27. Koton PA (1989) Using experience in learning and problem solving. PhD thesis (TR-441), Computer Science, Massachusetts Institute of Technology, MA

  28. Bradburn C, Zeleznikow J (1994) The application of case-based reasoning to the tasks of health care planning. In: Wess S, Althoff KD, Richter MM (eds) Proceedings topics in case-based reasoning: first European workshop, EWCBR-93. Springer, Berlin, pp 365–378

    Google Scholar 

  29. Marling C, Whitehouse D (2001) Case-based reasoning in the care of Alzheimer’s disease patients. In: Aha DW, Watson I (eds) Proceedings of the 4th international conference on casebased reasoning. Springer, Berlin, pp 702–715

    Google Scholar 

  30. Surma J, Vanhoof K (1995) Integration rules and cases for the classification task. In: Veloso M, Aamodt A (eds) Proceedings of the 1st international conference on case-based reasoning, Sesimbra, Portugal, October 1995. Lecture notes in computer science. Springer, Berlin, pp 325–334

    Google Scholar 

  31. Xu LD (1996) An integrated rule- and case-based approach to AIDS initial assessment. Int J Biomed Comput 40:197–207

    Article  Google Scholar 

  32. Branting LK, Porter BW (1991) Rules and precedents as complementary warrants. In: Proceedings of the 9th national conference on artificial intelligence, Anaheim, CA, July 1991. AAAI, Menlo Park

    Google Scholar 

  33. Bichindaritz I, Kansu E, Sullivan K (1998) Case-based reasoning in care-partner: Gathering evidence for evidence-based medical practice. In: Smyth B, Cunningham P (eds) Proceedings of the 4th European workshop on case-based reasoning, Dublin, Ireland, September 1998. Lecture notes in computer science, vol 1488. Springer, Berlin, pp 334–345

    Google Scholar 

  34. Macura R, Macura K (1995) Macrad: Radiology image resource with a cased-based retrieval system. In: Veloso M, Aamodt A (eds) Proceedings of the 1st international conference on CBR. Springer, Berlin, pp 43–54

    Google Scholar 

  35. Gierl L, Stengel-Rutkowski S (1994) Integrating consultation and semi-automatic knowledge acquisition in a prototype-based architecture: experiences with dysmorphic syndromes. Artif Intell Med 6:29–49

    Article  Google Scholar 

  36. Schmidt R, Montani S, Bellazzi R, Portinale L, Gierl L (2001) Case-based reasoning for medical knowledge-based systems. Int J Med Inf 64(2–3):355–367

    Article  Google Scholar 

  37. Bichindaritz I (2006) Memoire: A framework for semantic interoperability of case-based reasoning systems in biology and medicine. Artif Intell Med 36:177–192

    Article  Google Scholar 

  38. Funk P, Nilsson M, Xiong N (2005) Knowledge discovery and case based reasoning in medical applications with time series. In: Proceedings of the of the third workshop on case based reasoning in the health sciences, ICCBR 2005. DePaul University, Chicago, pp 42–51

    Google Scholar 

  39. Ramoni M, Sebastiani P (1997) The use of exogenous knowledge to learn Bayesian Networks for incomplete databases. In: Liu X, Cohen P, Berthold M (eds) Advances in intelligent data analysis. Springer, Berlin, pp 537–548

    Chapter  Google Scholar 

  40. Hovorka R, Svacina S, Carson ER, Williams CD, Sönksen PH (1996) A consultation system for insulin therapy. Comput Methods Programs Biomed 32:303–310

    Article  Google Scholar 

  41. Nucci G et al. (1999) Verification phase final report, T-IDDM deliverable 5.2. http://aim.unipv.it/projects/tiddm/ftp.html

  42. The Diabetes Control and Complication Trial Research Group (1993) The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. New Engl J Med 329:977–986

    Article  Google Scholar 

  43. Montani S, Bellazzi R (2000) Exploiting multi-modal reasoning for knowledge management and decision support: an evaluation study. In: Journal of the American medical informatics association (JAMIA) symposium supplement, pp 585–589

  44. Bellazzi R, Larizza C, Lanzola G (1999) An http-based server for temporal abstractions. In: Proceedings of the IDAMAP’99, pp 52–62

  45. Cases A, Coll E (2002) Chronic hypotension in the dialysis patient. J Nephrol 15:331–335

    Google Scholar 

  46. Tisler A, et al. (2002) Comparison of dialysis and clinical characteristics of patients with frequent and occasional hemodialysis-associated hypotension. Kidney Blood Press Res 25:97–102

    Article  Google Scholar 

  47. Portinale L, Montani S, Bottrighi A, Leonardi G, Juarez J (2006) A case-based architecture for temporal abstraction configuration and processing. Technical Report TR-INF-2006-05-02, Dipartimento di Informatica, Universita’ del Piemonte Orientale, Alessandria, Italy

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Informatica, Università del Piemonte Orientale, Alessandria, Italy

    Stefania Montani

Authors
  1. Stefania Montani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stefania Montani.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Montani, S. Exploring new roles for case-based reasoning in heterogeneous AI systems for medical decision support. Appl Intell 28, 275–285 (2008). https://doi.org/10.1007/s10489-007-0046-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10489-007-0046-2

Keywords

Search

Navigation