Graphical Modelling in Mental Health Risk Assessments

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dc.cclicenceN/Aen
dc.contributor.authorObembe, Funmi
dc.contributor.authorBuckingham, Christopher D
dc.date.accessioned2020-05-28T15:09:16Z
dc.date.available2020-05-28T15:09:16Z
dc.date.issued2010-11
dc.description.abstractProbabilistic models can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty. In this paper, we present the development of a chain graph for assessing the risks associated with mental health problems, which is a domain that has high amounts of inherent uncertainty. The Galatean mental health Risk and Social care Tool, GRiST, has been developed to support mental-health risk assessments by using a psychological model to represent the expertise of mental-health practitioners. It is a hierarchical knowledge structure based on fuzzy sets for reasoning with uncertainty. This paper describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise.en
dc.funderNo external funderen
dc.identifier.citationObembe O. and Buckingham C.D. (2010) Graphical Modelling in Mental Health Risk Assessment. The Second International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE 2010), November 21 – 26, Lisbon, Portugal. Conference proceedings published by XPS (Xpert Publishing Services)en
dc.identifier.isbn9781612081083
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/19653
dc.language.isoenen
dc.peerreviewedYesen
dc.publisherIARIAen
dc.subjectMental health risk assessmenten
dc.subjectProbablity graphsen
dc.subjectChain graphsen
dc.titleGraphical Modelling in Mental Health Risk Assessmentsen
dc.typeConferenceen

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