Argumentation-based dialogue systems for medical training

Adela Grando, Laura Moss, Gemma Bel-Enguix, M. Dolores Jiménez-López, John Kinsella

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Dialogue and argumentation have been applied to the field of Artificial Intelligence in the medical domain. Argueira (Grando et al., Argumentation-logic for explaining anomalous patient responses to treatments, 13th conference on Artificial Intelligence in Medicine (AIME 11). Springer, 35–44, 2011) is a system based on the ASPIC argumentation engine and is able to detect anomalous patient responses using flexible reasoning processes and logical argumentation. This paper introduces an extended arguEIRA with an argumentation-based dialogue system inspired by the system proposed by Parsons et al. (J Log Comput 13:347–376, 2003) and based on a variant of Dung’s calculus (Dung, Artif Intell 77:321–357, 1995). The aim is to achieve systems for medical training that provide human-like mechanisms for computer-clinician interaction, potentially enhancing the acceptance of the system's explanations while changing the clinician's behavior. Furthermore, we aim to provide clinicians with simple mechanisms to discover through the training process if the knowledge base used by the explanation system should be updated or corrected, potentially changing the training system's behavior.

Original languageEnglish (US)
Title of host publicationWhere Humans Meet Machines
Subtitle of host publicationInnovative Solutions for Knotty Natural-Language Problems
PublisherSpringer New York
Pages213-232
Number of pages20
ISBN (Electronic)9781461469346
ISBN (Print)9781461469339
DOIs
StatePublished - Jan 1 2013
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

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