Abstract
We present a new framework for combining logic with probability, and demonstrate the application of this framework to breast cancer prognosis. Background knowledge concerning breast cancer prognosis is represented using logical arguments. This background knowledge and a database are used to build a Bayesian net that captures the probabilistic relationships amongst the variables. Causal hypotheses gleaned from the Bayesian net in turn generate new arguments. The Bayesian net can be queried to help decide when one argument attacks another. The Bayesian net is used to perform the prognosis, while the argumentation framework is used to provide a qualitative explanation of the prognosis.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Amgoud, L., Cayrol, C., and Lagasquie-Schiex, M.-C., 2004, “On Bipolarity in Argumentation frameworks,” in: 10th International Workshop on Non-Monotonic Reasoning (NMR 2004) J.P. Delgrande and T. Schaub eds., Whistler, Canada, June 6–8, 2004, Proceedings. pp. 1–9.
A/S, H.E.: 1989, ‘Hugin’
Borak, J. and Veilleux, S., 1982, “Errors of intuitive logic among physicians,” Soc. Sci. Med. 16, 1939–1947.
Clark, P. and Niblett, T., 1987, “Induction in Noisy Domains,” in: Proceedings of the 2nd European Working Session on Learning. Bled Yugoslavia:. Sigma Press.
Cristofanilli, M., Hayes, D., Budd, G., Ellis, M., Stopeck, A., Reuben, J., Doyle, G., Matera, J., Allard, W., Miller, M., Fritsche, H., Hortobagyi, G., and Terstappen, L., 2005, “Circulating tumor cells: A novel prognostic factor for newly diagnosed metastatic breast cancer,” J Clin Oncol 23, 1420–1430.
Dung, P., 1995, “On the Acceptability of Arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games,” Artificial Intelligence 77, 321–357.
Fox, J. and Parsons, S., 1997, “On Using Arguments For Reasoning About Actions And Values,” in: Proc AAAI Spring Symposium on Qualitative Preferences in Deliberation and Practical Reasoning, Stanford.
Franklin, B., 1887, Collected Letters, Putnam New York.
Friedman, 2004, “Inferring cellular networks using probabilistic graphical models,” Science 303, 799–805.
Galea, M., Blamey, R., Elston, C.E., and Ellis, I., 1992, “The Nottingham Prognostic Index in primary breast cancer,” Breast Cancer Research and Treatment 3, 207–219.
Gard, R., 1961, Buddhism, George Braziller Inc New York.
Hunter, A. and Besnard, P., 2001, “A logic-based theory of deductive arguments,” Artificial Intelligence 128, 203–235.
Kahneman, D. and Tversky, A., 1973, “On the psychology of prediction,” Psychol. Rev. 80, 237–251.
Korb, K.B. and Nicholson, A.E., 2003, Bayesian Artificial Intelligence, London: Chapman and Hall / CRC Press.
Krause, P., Ambler, S., Elvang-Goranssan, M. and Fox, J., 1995, “A logic of argumentation for reasoning under uncertainty,” Computational Intelligence 11, 113–131.
McConachy, R., Korb, K.B., and Zukerman, I., 1998, “A Bayesian approach to automating argumentation,” in Proceedings of New Methods in Language Processing & Computational Natural Language Learning (NeMLaP3/CoNLL98) D.M.W. Powers ed., pp. 91–100.
McPherson, K., Steel, C., and Dixon, J.C., 2000, “Breast cancer: Epidemiology. Risk factors and Genetics,” BMJ 321, 624–628.
Michalski, R., Mozetic, I., Hong, J., and Lavrac, N., 1986, “The Multi-Purpose Incremental Learning System AQ15 and its Testing: Application to Three Medical Domains,” in: Proceedings of the Fifth National Conference on Artificial Intelligence, Philadelphia PA, pp. 1041–1045.
Parsons, S., 2003, “Order of magnitude reasoning and qualitative probability,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11(3), 373–390.
Parsons, S., 2004, “On precise and correct qualitative probabilistic reasoning,” International Journal of Approximate Reasoning 35, 111–135.
Pearl, J., 2000, Causality: Models, Reasoning, and Inference, Cambridge: Cambridge University Press.
Pollock, J.L., 1999, “Rational Cognition in OSCAR,” in: ATAL, pp. 71–90.
Poole, D., 2002, “Logical argumentation, abduction, and Bayesian decision theory: A Bayesian approach to logical arguments and its application to legal evidential reasoning,” Cardozo Law Review 22, 1733–1745.
Prakken, H. and Sartor, G., 1996, “Argument-based extended logic programming with defeasible priorities,” in Working Notes of 3rd ModelAge Workshop: Formal Models of Agents, P.-Y. Schobbens, ed., Sesimbra, Portugal.
Quinn, M. and Allen, E., 1995, “Changes in incidence of and mortality from breast cancer in England and Wales since introduction of screening,” BMJ 311, 1391–1395.
Richards, M., Smith, I., and Dixon, J., 1994, “Role of systemic treatment for primary operable breast cancer,” BMj 309, 1263–1366.
Ries, L., Eisner, M., Kosary, C., Hankey, B., Miller, B., Clegg, L., Mariotto, A., Feuer, E., and Edwards, B., 2004, SEER Cancer Statistics Review 1975-2001, National Cancer Institute.
Saha, S. and Sen, S., 2004, “A Bayes Net approach to Argumentation,” in: Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'04), Vol 3, 1436–1437.
Spirtes, P., Glymour, C., and Scheines, R., 1993, Causation, Prediction, and Search, Cambridge MA: MIT Press, second (2000) edition.
Sutton, D. and Fox, J., 2003, “The syntax and semantics of PROforma,” J Am Med Inform Assoc. 10(5), 433–443.
Veer, L., Paik, S., and Hayes, D., 2005, “Gene expression profiling of breast cancer: A new tumor marker,” J Clin Oncol. 23, 1631–1635.
Williamson, J., 2005, Bayesian nets and Causality: Philosophical and Computational Foundations, Oxford: Oxford University Press.
Wittig, F. and Jameson, A., 2000, “Exploiting Qualitatve Knowledge in the Learning of Conditional Probabilites of Bayesian Networks,” In: C. Boutilier and M. Goldszmidt (eds.): Uncertainty in Artificial Intelligence: Proceedings of the Sixteenth Conference.
Zwitter, M. and Soklic, M., 1988, “Breast Cancer Characteristics and Recurrence Data.”
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Williams, M., Williamson, J. Combining Argumentation and Bayesian Nets for Breast Cancer Prognosis. JoLLI 15, 155–178 (2006). https://doi.org/10.1007/s10849-005-9010-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10849-005-9010-x