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Using an Artificial Intelligence-Based Argument Theory to Generate Automated Patient Education Dialogues for Families of Children with Juvenile Idiopathic Arthritis
Benjamin Rose-Davis, William Van Woensel, Elizabeth Stringer, Samina Abidi, Syed Sibte Raza Abidi
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.
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