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Role of Knowledge Engineering in the Development of a Hybrid Knowledge Based Medical Information System for Atrial Fibrillation
Department of Mathematics, Jamia Millia Islamia University, New Delhi, India
Department of Computer science, Jamia Millia Islamia University, New Delhi, India
- 1 Department of Mathematics, Jamia Millia Islamia University, New Delhi, India
- 2 Department of Computer science, Jamia Millia Islamia University, New Delhi, India
American Journal of Industrial and Business Management·Volume 03 (2013)·Pages 36–41·Published 17 January 2013·DOI10.4236/ajibm.2013.31005
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Abstract
In this paper, we are describing role of knowledge engineering in the development of a hybrid knowledge based medical information system. Knowledge engineering plays important role in development of various technologies such as: expert systems, neural network, artificial intelligence, hybrid intelligent systems, data mining, decision support systems, and knowledge based systems etc. The hybrid medical information system mainly consists of medical information system and medical knowledge base systems. These poly techniques of knowledge engineering when integrated with hybrid techniques of intelligent systems for designing, implementing knowledge bases to deal with medical informational data of Atrial Fibrillation. Atrial Fibrillation is the most common heart rhythm disorder which increases the risk of mortality and morbidity.
KeywordsArtificial Intelligence (AI)Decision MakingKnowledge EngineeringKnowledge BaseMortalityMorbidityKnowledge Management (KM)Experience Management (EM)Knowledge Base System (KBS)Knowledge Management System (KMS)Atrial Fibrillation (AFib)Knowledge Discovery Techniques (KDT)Medical Information SystemMedical Information Based Decision MakingHybrid Intelligent Medical Information System (HIMIS)
- Z. Sun and G. Finnie, “Intelligent Techniques in E-Commerce: A Case-Based Reasoning Perspective,” Springer-Verlag, Heidelberg, 2004.
- R. Bergmann, “Experience Management: Foundations, Development Methodology and Internet-Based Applications,” Springer, Berlin, 2002.
- Z. Sun, “A Waterfall Model for Knowledge Management and Experience Management,” Proceedings of International Conference on Hybrid Intelligent Systems, Kitakyushu, 6-8 December 2004, pp. 472-475.
- H. Hasan and M. Handzic, “Australian Studies in Knowledge Management,” University of Wollongong Press, Wollongong, 2003.
- E. J. Benjamin, P. A. Wolf, R. B. D. Agostino, et al., “Impact of Atrial Fibrillation on the Risk of Death: The Framingham Heart Study,” Circulation, Vol. 98, No. 10, 1998, pp. 946-952.
- K. Lakshminarayan, C. A. Solid, A. J. Colins, et al., “Atrial Fibrillation and Stroke in the General Medicare Population—A 10-Year Perspective (1992 to 2002),” Stroke, Vol. 37, No. 8, 2006, pp. 1969-1974. doi:10.1161/01.STR.0000230607.07928.17
- P. A. Wolf, R. D. Abbott and W. B. Kanne, “Atrial Fibrillation as an Independent Risk Factor for Stroke: The Framingham Heart Study,” Stroke, Vol. 22, 1991, pp. 983-988. doi:10.1161/01.STR.22.8.983
- T. Thom, N. Haase, W. Rosamond, et al., “Heart Disease and Stroke Statistics—A Report from American Heart Association Statistics Committee and Stroke Statistics Subcommittee,” Circulation, Vol. 113, 2006, p. e85.
- K. E. Burn-Thornton, “Making the Most of Data in Order to Provide Accurate Clinical Decision Support Systems for the Use in the Determination of Heart Disease,” Proceeding of Third International Conference on Data Mining, Bologna, 25-27 September 2002, pp. 839-848.
- I. Watson, “Applying Case-Based Reasoning: Techniques for Enterprise Systems,” Morgan Kaufmann Publishers, San Francisco, 1997.
- J. Surma and K. Vanhoff, “Integrating Rules and Cases for ICCBR,” Lecture Notes in Artificial Intelligence 1010, Sesimbra, 1995.
- S. Montani, R. Bellazzi, L. Portinale, S. Fiocchi and M. A. Stefanelli, “Case-Based Retrieval System for Diabetic Patients Therapy,” Proceedings of IDAMAP 98 Working Notes, Workshop ECAI 98, Brighton, 1998, pp. 64-70.
- Z. Sun and G. Finnie, “Experience Based Reasoning for Recognizing Fraud and Deception,” Proceedings of International Conference on Hybrid Intelligent Systems (HIIS 2004), Kitakyushu, 6-8 December 2004, pp. 80-85.