Argumentation-logic for explaining anomalous patient responses to treatments

Maria Adela Grando, Laura Moss, David Glasspool, Derek Sleeman, Malcolm Sim, Charlotte Gilhooly, John Kinsella

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

5 Scopus citations

Abstract

The EIRA system has proved to be successful in the detection of anomalous patient responses to treatments in the Intensive Care Unit (ICU). One weakness of EIRA is the lack of mechanisms to describe to the clinicians, rationales behind the anomalous detections. In this paper, we extend EIRA by providing it with an argumentation-based justification system that formalizes and communicates to the clinicians the reasons why a patient response is anomalous. The implemented justification system uses human-like argumentation techniques and is based on real dialogues between ICU clinicians.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Medicine - 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Proceedings
Pages35-44
Number of pages10
DOIs
StatePublished - 2011
Externally publishedYes
Event13th Conference on Artificial Intelligence in Medicine, AIME 2011 - Bled, Slovenia
Duration: Jul 2 2011Jul 6 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6747 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th Conference on Artificial Intelligence in Medicine, AIME 2011
Country/TerritorySlovenia
CityBled
Period7/2/117/6/11

Keywords

  • argumentation logic
  • explanation
  • intensive care unit
  • knowledge-based expert systems
  • ontology

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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