Argumentation-logic for explaining anomalous patient responses to treatments

Authors:
Maria Adela Grando;Laura Moss;David Glasspool;Derek Sleeman;Malcolm Sim;Charlotte Gilhooly;John Kinsella
Affiliations:
School of Informatics, University of Edinburgh, UK;Academic Unit of Anaesthesia, Pain and Critical Care Medicine, School of Medicine, University of Glasgow, UK and Department of Computing Science, University of Aberdeen, UK and Department of Clini ...;School of Informatics, University of Edinburgh, UK;Academic Unit of Anaesthesia, Pain and Critical Care Medicine, School of Medicine, University of Glasgow, UK and Department of Computing Science, University of Aberdeen, UK;Academic Unit of Anaesthesia, Pain and Critical Care Medicine, School of Medicine, University of Glasgow, UK;Academic Unit of Anaesthesia, Pain and Critical Care Medicine, School of Medicine, University of Glasgow, UK;Academic Unit of Anaesthesia, Pain and Critical Care Medicine, School of Medicine, University of Glasgow, UK
Venue:
AIME'11 Proceedings of the 13th conference on Artificial intelligence in medicine
Year:
2011

Citing 6
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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.