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Context-Based Intelligent Service for Healthcare Applications

Context-Based Intelligent Service for Healthcare Applications

Alexander Smirnov, Tatiana Levashova
Copyright: © 2009 |Pages: 15
ISBN13: 9781605663562|ISBN10: 1605663565|EISBN13: 9781605663579
DOI: 10.4018/978-1-60566-356-2.ch009
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MLA

Smirnov, Alexander, and Tatiana Levashova. "Context-Based Intelligent Service for Healthcare Applications." Handbook of Research on Information Technology Management and Clinical Data Administration in Healthcare, edited by Ashish N. Dwivedi, IGI Global, 2009, pp. 128-142. https://doi.org/10.4018/978-1-60566-356-2.ch009

APA

Smirnov, A. & Levashova, T. (2009). Context-Based Intelligent Service for Healthcare Applications. In A. Dwivedi (Ed.), Handbook of Research on Information Technology Management and Clinical Data Administration in Healthcare (pp. 128-142). IGI Global. https://doi.org/10.4018/978-1-60566-356-2.ch009

Chicago

Smirnov, Alexander, and Tatiana Levashova. "Context-Based Intelligent Service for Healthcare Applications." In Handbook of Research on Information Technology Management and Clinical Data Administration in Healthcare, edited by Ashish N. Dwivedi, 128-142. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-356-2.ch009

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Abstract

The chapter presents an approach to implementation of an intelligent service for decision support in healthcare logistics taking an advantage of the knowledge logistics idea. The approach is based on synergistic integration of knowledge acquired from distributed sources in order to obtain new or complement insufficient knowledge. The approach is based on the methodology that assumes three levels of information integration. The application domain is described via an application ontology using the formalism of object-oriented constraint networks. The problem is represented by an abstract context that is obtained as a result of the slicing operation on the application ontology. Finally, filling the abstract context with up-to-date information about the current situation produces an operational context. Contexts of both types share the same knowledge representation formalism that is used by the application ontology. As a result the operational context can be considered as a constraint satisfaction problem. Solving this task produces feasible decisions in the current situation.

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