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Stud Health Technol Inform. 2019 Aug 21;264:1337-1341. doi: 10.3233/SHTI190444.

Using an Artificial Intelligence-Based Argument Theory to Generate Automated Patient Education Dialogues for Families of Children with Juvenile Idiopathic Arthritis.

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NICHE Research Group, Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
Division of Pediatric Rheumatology, IWK Health Centre, Halifax, Nova Scotia, Canada.
Department of Epidemiology and Population Health, Dalhousie University, Halifax, Nova Scotia, Canada.


Juvenile Idiopathic Arthritis (JIA) is the most common chronic rheumatic disease of childhood, with outcomes including pain, prolonged dependence on medications, and disability. Parents of children with JIA report being overwhelmed by the volume of information in the patient education materials that are available to them. This paper addresses this educational gap by applying an artificial intelligence method, based on an extended model of argument, to design and implement a dialogue system that allows users get the educational material they need, when they need it. In the developed system, the studied model of argument was leveraged as part of the system's dialogue manager. A qualitative evaluation of the system, using cognitive walkthroughs and semi-structured interviews with JIA domain experts, suggests that these methods show great promise for providing quality information to families of children with JIA when they need it.


Artificial Intelligence; Patient Education; Semantic Web

[Indexed for MEDLINE]

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