Modulating membership grades to gain consensus for fuzzy set uncertainty values in a clinical decision support system

Sherif E. Hegazy, Christopher D. Buckingham

Research output: Chapter in Book/Report/Conference proceedingConference publication

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 languageEnglish
Title of host publicationProceedings - The 3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services, CENTRIC 2010
PublisherIEEE
Pages40-45
Number of pages6
ISBN (Print)978-0-7695-4141-9
DOIs
Publication statusPublished - 2010
Event3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services - Nice, France
Duration: 22 Aug 201027 Aug 2010

Conference

Conference3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services
Abbreviated titleCENTRIC 2010
CountryFrance
CityNice
Period22/08/1027/08/10

Keywords

  • clinical decision support
  • concatenation
  • consensus
  • e-Health
  • expert systems
  • membership grades
  • mental health

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  • Cite this

    Hegazy, S. E., & Buckingham, C. D. (2010). Modulating membership grades to gain consensus for fuzzy set uncertainty values in a clinical decision support system. In Proceedings - The 3rd International Conference on Advances in Human-Oriented and Personalized Mechanisms, Technologies and Services, CENTRIC 2010 (pp. 40-45). IEEE. https://doi.org/10.1109/CENTRIC.2010.27