Abstract
This paper deals with Knowledge Engineering (KE), Clinical Decision Support Systems (CDSS), and Expert Systems (ES) as essential methods and tools supporting the Knowledge Management (KM) process in medicine. Specifically, we focus on the main component of the CDSS, knowledge base (KB). We demonstrate a hybrid approach to the creation, modification, verification, and validation of KB, which combines a fuzzy rule system with data mining. We describe the design and implementation of KB for two CDSS systems. The first system, which supports the evaluation of clinical depression, uses a combination of three methods: (1) creation of fuzzy rules based on expert clinicians’ knowledge and standard guidelines, (2) construction of Artificial Neural Networks (ANN) based on patients’ data, and (3) implementation of a CAKE (Computer Aided Knowledge Engineering) tool. The second system, which supports the diagnosis of obstructive sleep apnea, uses a combination of two methods: (1) creation of fuzzy rules derived from the medical literature and the expert clinicians’ knowledge and (2) induction of decision trees from large clinical data sets. Based on these two clinical studies, we demonstrate that KE methods should be regarded as valuable methods and tools which can be successfully used in medical KM for the creation, validation, and maintenance of KB.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Beardon, C. (ed.): Artificial Intelligence Terminology - A Reference Guide, p. 86. Wiley, New York (1989)
Berner, E.S., La Lande, T.J.: Overview of Clinical Decision Support Systems. In: Berner Eta, S. (ed.) Clinical Decision Support Systems. Theory and Practice. Health Information Series, pp. 3–22 (2007)
Carter, J.H.: Design and Implementation Issues. In: Berner Eta, S. (ed.) Clinical Decision Support Systems. Theory and Practice. Health Information Series, pp. 64–98 (2007)
Collop, N.A., Cassell, D.K.: Snoring and Sleep-disordered Breathing. In: Lee-Chiong, T., Sateia, M., Carskadon, M.A. (eds.) Sleep Medicine, pp. 349–355. Hanley & Belfus, Inc., Philadelphia (2002)
Finlay, P.N.: Introducing Decision Support Systems. Blackwell Publishers, Blackwell (1994)
Kaushal, R., Shojania, K.G., Bates, D.W.: Effects of Computerized Physician Order Entry and Clinical Decision Support Systems on Medication Safety: A systematic Review. Archives of Internal Medicine 163, 1409–1416 (2003)
von Michalik, K.: Selected Aspects of Multi-Level Hybrid AI Environment for Decision Support. Journal of Artificial Intelligence Studies (Special Issue)Â 1(2(24)) (2004); Proceedings of VI International Conference on Artificial Intelligence AI (2004)
Miller, R.A., Geissbuhler, A.: Diagnostic Decision Support Systems. In: Berner Eta, S. (ed.) Clinical Decision Support Systems. Theory and Practice. Health Information Series, pp. 99–125 (2007)
El Morr, C., Subercaze, J.: Knowledge Management in Health Care. In: Cruz-Cunha, M.M., Tavares, A.J., Simões, R.J. (eds.) Handbook of Research on Developments in e-Health and Telemedicine: Technological and Social Perspectives, pp. 490–510. Medical Information Science Reference, IGI Global, Hershey, PA (2010)
Power, D.J.: Decision Support Systems: Concepts and Resources for Managers. Quorum Books, Westport (2002)
Shabot, M.M., LoBue, M., Chen, J.: Wireless Clinical Alerts for Physiologic, Laboratory and Medication Data, Proceedings – AMIA Symposium. In: Journal of the American Medical Informatics Association, pp. 789–793 (2000)
Shapiro, S.C. (ed.): Encyclopedia of Artificial Intelligence, vol. 1, p. 287. Wiley, New York (1990)
Shortliffe, E.H.: Computer-Based Medical Consultations: MYCIN. Elsevier/North-Holland, Amsterdam, London (1976)
Spooner, S.A.: Mathematical Foundations of Decision Support Systems. In: Berner Eta, S. (ed.) Clinical Decision Support Systems. Theory and Practice. Health Information Series, pp. 23–43 (2007)
Waterman, D.A.: A Guide to Expert Systems, pp. 4–5. Addison-Wesley, Reading (1985)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
von Michalik, K., Kwiatkowska, M., Kielan, K. (2013). Application of Knowledge-Engineering Methods in Medical Knowledge Management. In: Seising, R., Tabacchi, M. (eds) Fuzziness and Medicine: Philosophical Reflections and Application Systems in Health Care. Studies in Fuzziness and Soft Computing, vol 302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36527-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-36527-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36526-3
Online ISBN: 978-3-642-36527-0
eBook Packages: EngineeringEngineering (R0)