An information-based bayesian approach to history taking
Effective history-taking systems need to dynamically reduce the number of questions to ask. This can be done either categorically or probabilistically, by exploiting previous patient's answers. In this paper, we propose a probabilistic information-based history-taking strategy that combines synergistically two information-content measures for reducing the number of questions asked. We have applied this strategy to an existing history-taking system and some preliminary results seem to confirm our initial intuitions.
KeywordsDisease Node History Taker Tension Headache Ambiguous Case Initial Intuition
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- 1.B. G. Buchanan, J. Moore, D. Forsythe, G. Carenini, G. Banks, and S. Ohlsson. Using medical informatics for explanation in the clinical setting. Technical Report CS-93-16, University of Pittsburgh, 1993. (To appear in the AI in Medicine journal).Google Scholar
- 2.G.F. Cooper. Current Research Direction in the Development of Expert Systems based on Belief Networks. Applied Stochastic Models and Data Analysis, 5:39–52, 1989.Google Scholar
- 3.G.F. Cooper. Bayesian belief-network inference using recursive decomposition. Technical Report KSL-90-05, Section of Medical Informatics, Stanford University, 1990.Google Scholar
- 5.J. Pearl. Probabilistic Reasoning in Intelligent Systems. Morgan Kaufman Publishers, Inc., 1988.Google Scholar
- 6.A.D. Poon, K.B. Johnson, and L.M Fagan. Augmented Transition Networks as a Representation for Knowledge-Based History-Taking Systems. In Proceedings of the 16th Symposium of Computer Applications in Medical Care, pages 762–766, 1992.Google Scholar
- 7.M. Pradhan et al. Knowledge Engineering for Large Belief Networks. In Proceedings of the 10th Conference on Uncertainty in Artificial Intelligence, pages 484–490, San Francisco, California, 1994. Morgan Kaufmann Publishers.Google Scholar
- 8.J.R. Saper et al. Handbook of Headache Management. Williams and Wilkins, 1993.Google Scholar
- 9.W.V. Slack. A history of Computerized Medical Interviews. M.D. Computing, 1(5):53–59, 1984.Google Scholar
- 10.S. Solomon and S. Fraccaro. The Headache Book. Consumers Union of United States, 1991.Google Scholar
- 11.S. Srinivas. A Generalization of the Noisy-OR Model. In Proceedings of the 9th Conference on Uncertainty in Artificial Intelligence, pages 208–215, Washington D.C., 1993. Morgan Kaufmann Publishers.Google Scholar