IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v9y1989i4p272-284.html
   My bibliography  Save this article

Automated Critiquing of Medical Decision Trees

Author

Listed:
  • Michael P. Wellman
  • Mark H. Eckman
  • Craig Fleming
  • Sharon L. Marshall
  • Frank A. Sonnenberg
  • Stephen G. Pauker

Abstract

The authors developed a decision tree-critiquing program (called BUNYAN) that identifies potential modeling errors in medical decision trees. The program's critiques are based on the structure of a decision problem, obtained from an abstract description specifying only the basic semantic categories of the model's components. A taxonomy of node and branch types supplies the primitive building blocks for representing decision trees. BUNYAN detects potential problems in a model by matching general pattern expressions that refer to these primitives. A small set of general principles justifies critiquing rules that detect four categories of potential structural problems: impossible strategies, dominated strategies, unaccountable violations of symmetry, and omission of apparently reasonable strategies. Although critiquing based on structure alone has clear limitations, principled structural analysis constitutes the core of a methodology for reasoning about decision models. Key words: decision trees; computer-assisted critiquing. (Med Decis Making 1989;9:272-284)

Suggested Citation

  • Michael P. Wellman & Mark H. Eckman & Craig Fleming & Sharon L. Marshall & Frank A. Sonnenberg & Stephen G. Pauker, 1989. "Automated Critiquing of Medical Decision Trees," Medical Decision Making, , vol. 9(4), pages 272-284, December.
  • Handle: RePEc:sae:medema:v:9:y:1989:i:4:p:272-284
    DOI: 10.1177/0272989X8900900407
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X8900900407
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X8900900407?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Curtis P. Langlotz & Edward H. Shortliffe & Lawrence M. Fagan, 1988. "A Methodology for Generating Computer-based Explanations of Decision-theoretic Advice," Medical Decision Making, , vol. 8(4), pages 290-303, December.
    2. Ross D. Shachter, 1986. "Evaluating Influence Diagrams," Operations Research, INFORMS, vol. 34(6), pages 871-882, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stephen G. Pauker & John B. Wong, 2005. "The Influence of Influence Diagrams in Medicine," Decision Analysis, INFORMS, vol. 2(4), pages 238-244, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:cup:judgdm:v:1:y:2006:i::p:162-173 is not listed on IDEAS
    2. Fernandez del Pozo, J. A. & Bielza, C. & Gomez, M., 2005. "A list-based compact representation for large decision tables management," European Journal of Operational Research, Elsevier, vol. 160(3), pages 638-662, February.
    3. Els Hannes & Diana Kusumastuti & Maikel Espinosa & Davy Janssens & Koen Vanhoof & Geert Wets, 2012. "Mental maps and travel behaviour: meanings and models," Journal of Geographical Systems, Springer, vol. 14(2), pages 143-165, April.
    4. Bielza, Concha & Gómez, Manuel & Shenoy, Prakash P., 2011. "A review of representation issues and modeling challenges with influence diagrams," Omega, Elsevier, vol. 39(3), pages 227-241, June.
    5. Zitrou, Athena & Bedford, Tim & Walls, Lesley, 2010. "Bayes geometric scaling model for common cause failure rates," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 70-76.
    6. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    7. Robert F. Nease JR, 1996. "Do Violations of the Axioms of Expected Utility Theory Threaten Decision Analysis?," Medical Decision Making, , vol. 16(4), pages 399-403, October.
    8. Prakash Shenoy, 1998. "Game Trees For Decision Analysis," Theory and Decision, Springer, vol. 44(2), pages 149-171, April.
    9. Lopez-Diaz, Miguel & Rodriguez-Muniz, Luis J., 2007. "Influence diagrams with super value nodes involving imprecise information," European Journal of Operational Research, Elsevier, vol. 179(1), pages 203-219, May.
    10. Oepping, Hardy, 2016. "Ein Bayes-Netz zur Analyse des Absturzrisikos im Gerüstbau [A Bayesian network for analysing the risk of falling from height in scaffolding]," MPRA Paper 73602, University Library of Munich, Germany.
    11. Mancuso, A. & Compare, M. & Salo, A. & Zio, E., 2021. "Optimal Prognostics and Health Management-driven inspection and maintenance strategies for industrial systems," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    12. David Rios Insua & Roi Naveiro & Victor Gallego, 2020. "Perspectives on Adversarial Classification," Mathematics, MDPI, vol. 8(11), pages 1-21, November.
    13. Borgonovo, Emanuele & Tonoli, Fabio, 2014. "Decision-network polynomials and the sensitivity of decision-support models," European Journal of Operational Research, Elsevier, vol. 239(2), pages 490-503.
    14. Bensi, Michelle & Kiureghian, Armen Der & Straub, Daniel, 2013. "Efficient Bayesian network modeling of systems," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 200-213.
    15. Groth, Katrina M. & Smith, Reuel & Moradi, Ramin, 2019. "A hybrid algorithm for developing third generation HRA methods using simulator data, causal models, and cognitive science," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Vic Hasselblad & Douglas C. McCrory, 1995. "Meta-analytic Tools for Medical Decision Making: A Practical Guide," Medical Decision Making, , vol. 15(1), pages 81-96, February.
    17. Concha Bielza & Prakash P. Shenoy, 1999. "A Comparison of Graphical Techniques for Asymmetric Decision Problems," Management Science, INFORMS, vol. 45(11), pages 1552-1569, November.
    18. Thwaites, Peter A. & Smith, Jim Q., 2018. "A graphical method for simplifying Bayesian games," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 3-11.
    19. Stephen G. Pauker & John B. Wong, 2005. "The Influence of Influence Diagrams in Medicine," Decision Analysis, INFORMS, vol. 2(4), pages 238-244, December.
    20. John M. Charnes & Prakash P. Shenoy, 2004. "Multistage Monte Carlo Method for Solving Influence Diagrams Using Local Computation," Management Science, INFORMS, vol. 50(3), pages 405-418, March.
    21. Barry R. Cobb, 2007. "Influence Diagrams with Continuous Decision Variables and Non-Gaussian Uncertainties," Decision Analysis, INFORMS, vol. 4(3), pages 136-155, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:9:y:1989:i:4:p:272-284. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.