ST Algorithm for Medical Diagnostic Reasoning

 

Irosh Fernando¹ and Frans A. Henskens²

 

¹ School of Electrical Engineering and Computer Science, University of Newcastle, NSW 2308, Australia (phone: +61 423 281 664; e-mail: irosh.fernando@uon.edu.au).

² School of Electrical Engineering and Computer Science, University of Newcastle, NSW 2308, Australia (e-mail: frans.henskens@newcastle.edu.au).

 

Manuscript received August 6, 2013.
Accepted for publication on September 30, 2013.

 

Abstract

The authors have previously described an approach for medical diagnostic reasoning based on the ST (Select and Test) model introduced by Ramoni and Stefanelli et al. This paper extends the previous approach by introducing the required algorithm for medical expert system development. The algorithm involves a bottom-up and recursive process using logical inferences, abduction, deduction, and induction. Pseudocode for the algorithm, and the data structures involved, are described, and the algorithm's implementation using a small sample knowledgebase and programmed in Java is included in appendixes. Implementation of a successful expert system is a challenging process; development of the necessary algorithm for its inference engine, and definition of a knowledgebase structure that models expert diagnostic reasoning and knowledge, only fulfils the initial step. Challenges associated with the remaining steps of the development process can be identified and dealt with using the CLAP software process model.

Key words: Medical diagnostic reasoning, medical expert systems, ST model.

  

DESCARGAR ARTÍCULO EN FORMATO PDF

 

References

[1] D. A. Wolfram, "An appraisal of INTERNIST-I," Artificial Intelligence in Medicine, vol. 7, pp. 93-116, 1995.         [ Links ]

[2] H. Mandin, A. Jones, W. Woloschuk, and P. Harasym, "Helping students learn to think like experts when solving clinical problems," Academic Medicine, vol. 72, pp. 173-179, 1997.         [ Links ]

[3] A. S. Elstein, L. S. Shulman, and S. A. Sprafka, Medical Problem-Solving: an Analysis of Clinical Reasoning: Cambridge, MA: Harvard University Press 1978.         [ Links ]

[4] E. Hunt, "Cognitive Science: Definition, Status, and Questions " Annual Review of psychology, vol. 40, pp. 603-629 1989.         [ Links ]

[5] G. R. Norman, C. L. Coblentz, L. R. Brooks, and C. J. Babcook, "Expertise in visual diagnosis - a review of the literature.," Academic Medicine, vol. 66(suppl), pp. s78-s83, 1992.         [ Links ]

[6] J. A. Reggia and Y. Peng, "Modeling diagnostic reasoning: a summary of parsimonious covering theory," Computer Methods and Programs in Biomedicine, vol. 25, pp. 125-134, 1987.         [ Links ]

[7] P. M. Wormian, "Medical Diagnosis: An Information-Processing Approach," Computers and Biomedical Research, vol. 5, pp. 315-328, 1972.         [ Links ]

[8] J. Stausberg and M. Person, "A process model of diagnostic reasoning in medicine," International Journal of Medical Informatics, vol. 54, pp. 9-23, 1999.         [ Links ]

[9] E. H. Shortliffe and B. G. Buchanan, "A model of inexact reasoning in medicine," Mathematical Biosciences, vol. 23, pp. 351-379, 1975.         [ Links ]

[10] S. Andreassen, F. V. Jensen, and K. G. Olesen, "Medical expert systems based on causal probabilistic networks," International Journal of Bio-Medical Computing, vol. 28, pp. 1-30, 1991.         [ Links ]

[11] T. Chard and E. M. Rubenstein, "A model-based system to determine the relative value of different variables in a diagnostic system using Bayes theorem," International Journal of Bio-Medical Computing, vol. 24, pp. 133-142, 1989.         [ Links ]

[12] B. S. Todd, R. Stamper, and P. Macpherson, "A probabilistic rule-based expert system," International Journal of Bio-Medical Computing, vol. 33, pp. 129-148, 1993.         [ Links ]

[13] K. Boegl, K. P. Adlassnig, Y. Hayashi, T. E. Rothenfluh, and H. Leitich, "Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system," Artificial Intelligence in Medicine, vol. 30, pp. 1-26, 2004.         [ Links ]

[14] L. Godo, R. L. de Mantaras, J. Puyol-Gruart, and C. Sierra, "Renoir, Pneumon-IA and Terap-IA: three medical applications based on fuzzy logic," Artificial Intelligence in Medicine, vol. 21, pp. 153-162, 2001.         [ Links ]

[15] T. Vetterlein and A. Ciabattoni, "On the (fuzzy) logical content of CADIAG-2," Fuzzy Sets and Systems, vol. 161, pp. 1941-1958, 2010.         [ Links ]

[16] I. Fernando, F. Henskens, and M. Cohen, "An Approximate Reasoning Model for Medical Diagnosis," in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. vol. 492, R. Lee, Ed., ed: Springer International Publishing, 2013, pp. 11-24.         [ Links ]

[17] M. Ramoni, M. Stefanelli, L. Magnani, and G. Barosi, "An epistemological framework for medical knowledge-based systems " IEEE Transactions on Systems, Man and Cybernetics, vol. 22, pp. 1361-1375, 1992.         [ Links ]

[18] I. Fernando, F. Henskens, and M. Cohen, "A Collaborative and Layered Approach (CLAP) for Medical Expert System Development: A Software Process Model," in IEEE/ACIS 11th International Conference on Computer and Information Science (ICIS12), 2012, pp. 497-502.         [ Links ]

[19] C. S. Peirce, "Illustrations of the logic of science, sixth paper-deduction, induction, hypothesis," The Popular Science Monthly, vol. 1, pp. 470-482, 1878.         [ Links ]

[20] American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders: DSM-5: American Psychiatric Publishing Incorporated, 2013.         [ Links ]

[21] I. Fernando, M. Cohen, and F. Henskens, "A systematic approach to clinical reasoning in psychiatry," Australasian Psychiatry, vol. 21, pp. 224-230,2013.         [ Links ]

[22] E. L. Kinney, "Medical Expert Systems - Who needs them ?," CHEST, vol. 91, pp. 3-4, 1987.         [ Links ]

[23] A. K. Das, "Computers in Psychiatry: A Review of Past Programs and an Analysis of Historical Trends," Psychiatric Quarterly, vol. 73, pp.351-365,2002.         [ Links ]

[24] D. Richards, "Collaborative Knowledge Engineering: Socialising Expert Systems," in 11th International Conference on Computer Supported Cooperative Work in Design, 2007.         [ Links ]