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dc.contributor.authorHadzic, Maja
dc.contributor.authorChen, Meifania
dc.contributor.authorBrouwer, R.
dc.contributor.editorAmandeep Sidhu and Tharam Dillon
dc.identifier.citationHadzic, Maja and Chen, Meifania and Brouwer, Rick. 2009. Completing the total wellbeing puzzle using a multi-agent system, in Amandeep Sidhu and Tharam Dillon (ed), Biomedical data and applications. pp. 281-293. Heidelberg: Springer.

Our research focus is the implementation of agent-based systems within the health domain, more specifically, in the study of total wellbeing. We use an evidence-based total wellbeing ontological model where the total well-being is seen as a function of physical health, mental health, emotions, relation-ships, financial situation and spirituality. We use the TICSA methodology to design a multi-agent system. This multi-agent system is based on the Total Wellbeing Ontology and helps intelligent retrieval, management and analysis of information related to total wellbeing. We hope this system to expose evidence that will support general public in managing their personal wellbeing better, and health professionals in adapting their services to address patients needs more systematically and effectively.

dc.subjectMulti-agent System Design
dc.subjectTotal Wellbeing
dc.subjectOntology-based Multi-agent System
dc.subjectHealth Information System
dc.titleCompleting the total wellbeing puzzle using a multi-agent system
dc.typeBook Chapter
dcterms.source.titleBiomedical data and applications

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curtin.departmentDigital Ecosystems and Business Intelligence Institute (DEBII)
curtin.accessStatusFulltext not available
curtin.facultyCurtin Business School
curtin.facultyThe Digital Ecosystems and Business Intelligence Institute (DEBII)

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