Evidence combination for incremental decision-making processes

Ghita Berrada, Maurice van Keulen, Ander de Keijzer

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Abstract

The establishment of a medical diagnosis is an incremental process highly fraught with uncertainty. At each step of this painstaking process, it may be beneficial to be able to quantify the uncertainty linked to the diagnosis and steadily update the uncertainty estimation using available sources of information, for example user feedback, as they become available. Using the example of medical data in general and EEG data in particular, we show what types of evidence can affect discrete variables such as a medical diagnosis and build a simple and computationally efficient evidence combination model based on the Dempster-Shafer theory.
Original languageUndefined
Place of PublicationEnschede
PublisherCentre for Telematics and Information Technology (CTIT)
Number of pages43
Publication statusPublished - Jan 2016

Publication series

NameCTIT technical report
PublisherUniversity of Twente, Centre for Telematics and Information Technology (CTIT)
No.CTIT-TR-16-01
ISSN (Print)1381-3625

Keywords

  • IR-99125
  • Dempster-Shafer evidence theory
  • EWI-26698
  • incremental decision-making processes
  • METIS-315164
  • user feedback
  • evidence combination
  • Uncertain databases

Cite this

Berrada, G., van Keulen, M., & de Keijzer, A. (2016). Evidence combination for incremental decision-making processes. (CTIT technical report; No. CTIT-TR-16-01). Enschede: Centre for Telematics and Information Technology (CTIT).