Table of Contents Author Guidelines Submit a Manuscript
Journal of Healthcare Engineering
Volume 2, Issue 2, Pages 241-258
Research Article

Modeling Medical Diagnosis Using a Comprehensive Cognitive Architecture

Stephen Strain1 and Stan Franklin2

1Department of Biomedical Engineering, University of Memphis, Memphis, TN, USA
2Department of Computer Science, University of Memphis, Memphis, TN, USA

Received 1 July 2010; Accepted 1 December 2010

Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Franklin and F. G. Patterson Jr., “The LIDA Architecture: Adding New Modes of Learning to an Intelligent, Autonomous, Software Agent,” Integrated Designs and Process Technology IDPT-2006, Society for Design and Process Science, San Diego.
  2. J. Zacks, N. Speer, K. Swallow et al., “Event Perception: A Mind-Brain Perspective,” Psychological Bulletin, vol. 133, no. 2, pp. 273–293, 2007. View at Google Scholar
  3. G. Drescher, Made Up Minds: A Constructivist Approach to Artificial Intelligence, MIT Press, Cambridge, 1991.
  4. P. Maes, “How to Do the Right Thing,” Connection Science, vol. 1, no. 3, pp. 291–323, 1989. View at Google Scholar
  5. V. L. Patel, E. H. Shortliffe, M. Stefanelli et al., “The Coming of Age of Artificial Intelligence in Medicine,” Artificial Intelligence in Medicine, vol. 46, no. 1, pp. 5–17, May 2009. View at Google Scholar
  6. J. P. Kassirer, J. B. Wong, and R. I. Kopelman, Learning Clinical Reasoning, Williams & Wilkins, Baltimore, 2nd edition, 2010.
  7. V. Patel, J. F. Arocha, and J. Zhang, “Thinking and Reasoning in Medicine,” in Cambridge Handbook of Thinking and Reasoning, Keith Holyoak, Ed., Cambridge University Press, Cambridge, UK, 2005. View at Google Scholar
  8. Dorland's Illustrated Medical Dictionary, W. B. Saunders Co., Philadelphia, 28th edition, 1994.
  9. A. S. Elstein and A. Schwarz, “Clinical problem solving and diagnostic decision making: selective review of the cognitive literature,” BMJ, vol. 324, pp. 729–732, March 23, 2002. View at Google Scholar
  10. A. Schwartz and A. S. Elstein, “Clinical reasoning in medicine,” in ClInical ReasonIng In the Health Professions, Joy Higgs, Mark A. Jones, Stephen Loftus, and Nicole Christensen, Eds., pp. 223–234, Elsevier, Amsterdam, 3rd edition, 2008. View at Google Scholar
  11. A. S. Elstein, “Thinking about diagnostic thinking: a 30-year perspective,” Advances in Health Science Education, vol. 14, pp. 7–18, 2009. View at Google Scholar
  12. R. S. Ledley and L. B. Lusted, “Reasoning Foundations of Medical Diagnosis,” Science, vol. 130, no. 3366, pp. 9–21, July 3, 1959. View at Google Scholar
  13. G. Parmigiani, Modeling in Medical Decision Making: A Bayesian Approach, John Wiley & Sons, New York, 2002.
  14. P. Szolovits and S. G. Pauker, “Categorical and Probabilistic Reasoning in Medical Diagnosis,” Artificial Intelligence, vol. 11, pp. 115–144, 1978. View at Google Scholar
  15. B. G. Buchanan and E. H. Shortliffe, Eds., Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project, Addison-Wesley Pub. Co., Reading, Mass, 1984.
  16. S. G. Pauker, G. A. Gorry, J. P. Kassirer, and W. B. Schwartz, “Towards the Simulation of Clinical Cognition: Taking a Present Illness by Computer,” The American Journal of Medicine, vol. 60, pp. 981–995, June 1976. View at Google Scholar
  17. M. J. Feldman, “Diagnostic Decision Support,” in Pediatric Informatics: Computer Applications in Child Health, Christoph U. Lehmann, George R. Kim, and Kevin B. Johnson, Eds., Chapter 12, pp. 161–172, Springer, New York, 2009. View at Google Scholar
  18. S. Bakken, L. M. Currie, N. Lee et al., “Integrating Evidence into Clinical Information Systems for Nursing Decision Support,” International Journal of Medical Informatics, vol. 77, no. 6, pp. 413–420, June 2008. View at Google Scholar
  19. W. L. Galanter, D. B. Hier, C. Jao, and D. Sarne, “Computerized physician order entry of medications and clinical decision support can improve problem list documentation compliance,” International Journal of Medical Informatics, vol. 79, no. 5, pp. 332–338, May 2010. View at Google Scholar
  20. A. X. Garg, N. K. J. Adhikari, H. McDonald et al., “Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes,” JAMA, vol. 293, no. 10, pp. 1223–1238, March 9, 2005. View at Google Scholar
  21. P. L. Elkin, M. Liebow, B. A. Bauer et al., “The introduction of a diagnostic decision support system (DXplainTM) into the workflow of a teaching hospital service can decrease the cost of service for the diagnostically challenging Diagnostic Related Groups (DRGs),” International Journal of Medical Informatics, vol. 79, no. 11, pp. 772–777, November 2010. View at Google Scholar
  22. S. Franklin, A. Kelemen, and L. McCauley, “IDA: A Cognitive Agent Architecture,” in IEEE Conf on Systems, Man and Cybernetics, pp. 2646–2651, IEEE Press, 1998.
  23. S. Franklin and L. McCauley, “Interacting with IDA,” in Agent Autonomy, H. Hexmoor, C. Castelfranchi, and R. Falcone, Eds., pp. 159–186, Kluwer, Dordrecht, 2003. View at Google Scholar
  24. B. J. Baars, In the theater of Consciousness: the Workspace of the Mind, Oxford University Press, Inc., New York, 1997.
  25. M. A. Conway, “Sensory-perceptual episodic memory and its context: autobiographical memory,” Philosophical Transactions of the Royal Society of London, Series B, (Biological Sciences), vol. 356, pp. 1375–1384, 2001. View at Google Scholar
  26. S. Franklin, B. J. Baars, U. Ramamurthy, and M. Ventura, “The Role of Consciousness in Memory,” Brains, Minds and Media, vol. 1, pp. 1–38, 2005. View at Google Scholar
  27. B. J. Baars and S. Franklin, “How conscious experience and working memory interact,” Trends in Cognitive Sciences, vol. 7, pp. 166–172, 2003. View at Google Scholar
  28. A. Negatu and S. Franklin, “An action selection mechanism for ‘conscious’ software agents,” Cognitive Science Quarterly (2002), vol. 2, pp. 363–386, 2002, Special issue on, “Desires, goals, intentions, and values: Computational architectures” with guest editors Maria Miceli and Cristiano Castelfranchi. View at Google Scholar
  29. S. Franklin, U. Ramamurthy, S. K. D'Mello et al., “LIDA: A Computational Model of Global Workspace Theory and Developmental Learning,” in AAAI Fall Symposium on AI and Consciousness: Theoretical Foundations and Current Approaches, AAAI, Arlington, Virginia, 2007.
  30. M. Minsky, The Society of Mind, Simon & Schuster, New York, 1985.
  31. P. Kanerva, “Sparse Distributed Memory and Related Models,” in Associative Neural Memories: Theory and Implementation, M. H. Hassoun, Ed., pp. 50–76, Oxford University Press, New York, 1993. View at Google Scholar
  32. S. Franklin and D. Jones, “A Triage Information Agent (TIA) based on the IDA Technology,” in AAAI Fall Symposium on Dialogue Systems for Health Communication, American Association for Artificial Intelligence, Washington, DC, 2004.
  33. L. B. Lusted, Introduction to Medical Decision Making, Charles C. Thomas, Springfield, 1968.
  34. S. Franklin, “Automating Human Information Agents,” in Practical Applications of Intelligent Agents, Z. Chen and L. C. Jain, Eds., pp. 27–58, Springer-Verlag, Berlin, 2001. View at Google Scholar