Argumentation-logic for creating and explaining medical hypotheses

Authors:
Maria Adela Grando;Laura Moss;Derek Sleeman;John Kinsella
Affiliations:
Division of Biomedical Informatics, School of Medicine, University California San Diego, 9500 Gilman Drive #0505, La Jolla, CA 92093-0505, USA;Academic Unit of Anaesthesia, Pain, and Critical Care Medicine, School of Medicine, University of Glasgow, Wolfson Medical School Building, University Avenue, Glasgow G12 8QQ, Scotland, UK and Dep ...;Academic Unit of Anaesthesia, Pain, and Critical Care Medicine, School of Medicine, University of Glasgow, Wolfson Medical School Building, University Avenue, Glasgow G12 8QQ, Scotland, UK and Dep ...;Academic Unit of Anaesthesia, Pain, and Critical Care Medicine, School of Medicine, University of Glasgow, Wolfson Medical School Building, University Avenue, Glasgow G12 8QQ, Scotland, UK
Venue:
Artificial Intelligence in Medicine
Year:
2013

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Abstract

Objective: While EIRA has proved to be successful in the detection of anomalous patient responses to treatments in the Intensive Care Unit, it could not describe to clinicians the rationales behind the anomalous detections. The aim of this paper is to address this problem. Methods: Few attempts have been made in the past to build knowledge-based medical systems that possess both argumentation and explanation capabilities. Here we propose an approach based on Dung's seminal calculus of opposition. Results: We have developed a new tool, arguEIRA, which is an extension of the existing EIRA system. 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. Conclusion: Our comparative evaluation of the EIRA system against the newly developed tool highlights the multiple benefits that the use of argumentation-logic can bring to the field of medical decision support and explanation.