Abstract
This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions.
Original language | English |
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Title of host publication | Proceedings - The 3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services, CENTRIC 2010 |
Publisher | IEEE |
Pages | 40-45 |
Number of pages | 6 |
ISBN (Print) | 978-0-7695-4141-9 |
DOIs | |
Publication status | Published - 2010 |
Event | 3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services - Nice, France Duration: 22 Aug 2010 → 27 Aug 2010 |
Conference
Conference | 3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services |
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Abbreviated title | CENTRIC 2010 |
Country/Territory | France |
City | Nice |
Period | 22/08/10 → 27/08/10 |
Keywords
- clinical decision support
- concatenation
- consensus
- e-Health
- expert systems
- membership grades
- mental health