Abstract
Probabilistic 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.
| Original language | English |
|---|---|
| Title of host publication | The Second International Conference on Advanced Cognitive Technologies and Applications (COGNITIVE 2010), November 21 – 26, Lisbon, Portugal |
| Editors | Ali Beklen, Jorge Ejarque, Wolfgang Gentzsch, Teemu Kanstren, Arne Kosche, Yong Woo Lee, Li Li, Michal Zemlicka |
| Publisher | IARIA |
| Pages | 72-77 |
| Number of pages | 6 |
| ISBN (Print) | 978-1-61208-108-3 |
| Publication status | Published - 26 Nov 2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Fingerprint
Dive into the research topics of 'Graphical Modelling in Mental Health Risk Assessment'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver