Ontology-Based Support for Human Disease Study

Hadzic, Maja; Chang, Elizabeth

doi:10.1109/hicss.2005.472

Cited by 34 publications

(25 citation statements)

References 13 publications

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“…The need for design a multi-agent system for the purpose of dynamic information retrieval regarding common knowledge of human diseases has been explained in [1,11]. Providing a systematic overview of the different aspects of human disease will bring a significant contribution to the advancement of human disease research and practice.…”

Section: A Multi-agent Systems In Medical Domainmentioning

confidence: 99%

“…We propose a distributed multi-agent system with the agents as its processing nodes [1]. The agents of GHDObased MAS are sociable.…”

Section: B Generic Human Disease Ontology (Ghdo)-based Masmentioning

confidence: 99%

“…Use of agent-based systems enables us to propose and design intelligent and dynamic medical information systems [1]. One of the main advantages of agents is their autonomy.…”

Section: Introductionmentioning

confidence: 99%

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Use and Modeling of Multi-agent Systems in Medicine

Hadzic

Dillon

2009

2009 20th International Workshop on Database and Expert Systems Application

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Abstract-Multi-Agent System (MAS), and more specifically, ontology-based MAS, are increasingly being proposed and used within the medical domain. In this paper we represent an ontology-based multi-agent system specifically designed to intelligently retrieve information about human diseases. The human disease ontology is organized according to the four dimensions: disease types, symptoms, causes and treatments. The multi-agent system consists of four different types of agent: Interface, Manger, Information and Smart agent. We use of UML 2.1 to model social and goal-driven nature of agents. We believe that UML 2.1 has not only provided a way for standardized notation of MAS, but also for effective representation of the dynamic processes associated with these MAS.Keywords-UML, modeling of multi-agent systems, ontologybased multi-agent systems, information retrieval.

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Section: A Multi-agent Systems In Medical Domainmentioning

confidence: 99%

“…We propose a distributed multi-agent system with the agents as its processing nodes [1]. The agents of GHDObased MAS are sociable.…”

Section: B Generic Human Disease Ontology (Ghdo)-based Masmentioning

confidence: 99%

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Use and Modeling of Multi-agent Systems in Medicine

Hadzic

Dillon

2009

2009 20th International Workshop on Database and Expert Systems Application

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“…To understand the mechanism behind these different operations we refer the interested reader to [12,15].…”

Section: Fig 9 Gmio-based Multi-agent Systemmentioning

confidence: 99%

Web Semantics for Intelligent and Dynamic Information Retrieval Illustrated within the Mental Health Domain

Hadzic

Chang

2008

Advances in Web Semantics I

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Abstract. Much of the available information covering various knowledge domains is distributed across various information resources. The issues of distributed and heterogeneous information that often come without semantics, lack an underlying knowledge base or autonomy, and are dynamic in nature of are hindering efficient and effective information retrieval. Current search engines that are based on syntactic keywords are fundamental for retrieving information often leaving the search results meaningless. Increasing semantics of web content (web semantics) would solve this problem and enable the web to reach its full potential. This would allow machines to access web content, understand it, retrieve and process the data automatically rather then only display it. In this paper we illustrate how the ontology and multi-agent system technologies which underpin this vision can be effectively implemented within the mental health domain. The full realisation of this vision is still to come.

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“…Therefore, there were some models proposed for such undertaking. [14] designed an ontology model, called Generic Human Disease Ontology (GHDO), that relates diseases to symptoms (phenotypes) and to the other three elements that uniquely identify a disease: disease type, causes, and treatments. However, no GHDO ontology has been published from the proposed model.…”

Section: Critical Review Most Of the Previous Work Assume That Herbsmentioning

confidence: 99%