Abstract
Medical guidelines provide knowledge about processes that is not directly suitable for building clinical decision-support systems. We discuss a two-step approach where knowledge from a guideline on COPD is translated into temporal logic, and augmented with physiological background knowledge. This allows capturing the dynamics of the processes using qualitative knowledge, while maintaining the temporal nature of the processes. As a second step, this represented clinical knowledge is translated into a decision-theoretic framework. We thus present a representation that can act as a basis for the construction of a decision-support system concerning monitoring of COPD.
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References
Hommersom, A., Groot, P., Lucas, P., Balser, M., Schmitt, J.: Verification of medical guidelines using background knowledge in task networks. IEEE Transactions on Knowledge and Data Engineering (2007)
Lucas, P.: Quality checking of medical guidelines through logical abduction. In: Proceedings of AI-2003 Research and Development in Intelligent Systems XX (2003)
Viegi, G., Pistelli, F., Sherrill, D., Maio, S., Baldacci, S., Carrozzi, L.: Definition, epidemiology and natural history of COPD. Eur. Respir. J. (2007)
GOLD: Global Initiative for Obstructive Lung Disease, http://www.goldcopd.com
Knublauch, H., Ferguson, R., Noy, N., Musen, M.: The Protégé OWL plugin: An open development environment for semantic web applications. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 229–243. Springer, Heidelberg (2004)
Artale, A., Franconi, E.: A survey of temporal extensions of description logics. Annals of Mathematics and Artificial Intelligence (2000)
Wolter, F., Zakharyaschev, M.: Temporalizing description logics. In: Proceedings of FroCoS 1998 (1998)
Jensen, F.V., Nielsen, T.D.: Bayesian Networks and Decision Graphs. Springer, Heidelberg (2007)
Wellman, M.: Fundamental concepts of qualitative probabilistic networks. Artificial Intelligence (1990)
Pearl, J.: Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, San Francisco (1988)
Hommersom, A., Lucas, P., van Bommel, P.: Checking the quality of clinical guidelines using automated reasoning tools. Theory and Practice of Logic Programming (2008)
Miksch, S., Shahar, Y., Johnson, P.: Asbru: a task-specific, intention-based, and time-oriented language for representing skeletal plans. In: KEML 1997: 7th Workshop on Knowledge Engineering: Methods & Languages (1997)
Fox, J., Johns, N., Lyons, C., Rahmanzadeh, A., Thomson, R., Wilson, P.: PROforma: a general technology for clinical decision support systems. Computer Methods and Programs in Biomedicine (1997)
Terenziani, P., Molino, G., Torchio, M.: A modular approach for representing and executing clinical guidelines. Artificial Intelligence in Medicine (2001)
de Raedt, L., Kersting, K.: Probabilistic logic learning. SIGKDD Explorations Newsletter (2003)
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van der Heijden, M., Lucas, P.J.F. (2010). Extracting Qualitative Knowledge from Medical Guidelines for Clinical Decision-Support Systems. In: Riaño, D., ten Teije, A., Miksch, S., Peleg, M. (eds) Knowledge Representation for Health-Care. Data, Processes and Guidelines. KR4HC 2009. Lecture Notes in Computer Science(), vol 5943. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11808-1_9
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DOI: https://doi.org/10.1007/978-3-642-11808-1_9
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