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Holonic multi-agent system complemented by human disease ontology supporting bio-medical community

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Open access
Authors
Hadzic, Maja
Chang, Elizabeth
Date
2005
Type
Conference Paper

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Citation
Hadzic, Maja and Chang, Elizabeth. 2005. : Holonic multi-agent system complemented by human disease ontology supporting bio-medical community, IEEE International Conference on Computational Intelligence: Methods and Applications (CIMA), Dec 15 2005. Istanbul, Turkey: IEEE.
Source Title
2005 ICSC Congress on Computational Intelligence: Methods and Applications (CIMA)
Source Conference
IEEE International Conference on Computational Intelligence: Methods and Applications (CIMA)
Faculty
Curtin Business School
School of Information Systems
School
Centre for Extended Enterprises and Business Intelligence
Remarks

Copyright 2005 IEEE

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Abstract

The medical milieu is an open environment characterized by a variety of distributed, heterogeneous and autonomous information resources. Coordination, cooperation and exchange of information are important to the medical community. This paper presents an Ontology-based Holonic Multiagent System that combines the advantages of the holonic paradigm with multi-agent system technology and ontology design, in order to realize a highly reliable, adaptive, scalable, flexible and robust diagnostic system for diseases. We design a new ontology, called Generic Human Disease Ontology (GHDO), for the representation of knowledge regarding human diseases. The concepts of the GHDO ontology are organized into the following four dimensions: Types, Symptoms, Causes and Treatments of human diseases. The holonic multi-agent system uses this common GHDO ontology for purpose of query formulation, information retrieval and information integration. This intelligent dynamic system provides opportunities to collect information from multiple information resources, to share data efficiently and to integrate and manage scientific results in a timely manner. We believe such a technique is expected to become the norm once existing resources (e.g. disease databases) will have become unlocked semantically through annotation with a shared ontology.