Abstract
Attention-deficit hyperactivity disorder (ADHD) is a prevalent neuropsychiatric disorder in both children and adults, characterized by symptoms of inattention, hyperactivity, and impulsiveness. Diagnosis is currently made using a battery of examinations, rating scales, and interviews. Many of these sources are subjective and not always correlated. The questionable reliability of these sources highlights the need for more objective tests of ADHD. In this chapter, we address this need with the design, development and testing of an efficient computational system for differentiation based on altered control of saccadic eye movements in ADHD subjects and a control group. Our hypothesis is that there is sufficient predictive information contained in existing eye movement data to allow for the development of a knowledge-based system that could be used to identify meaningful groups of ADHD subjects. Specifically, a case-based reasoning (CBR) system was implemented to retrieve and apply previous ADHD diagnostic cases to novel problems based on saccade performance data. An iterative refinement methodology was used to incrementally improve the CBR system, resulting in a tool that could distinguish ADHD from normal control subjects with an accuracy of over 70 subjects incorrectly classified by the CBR system were shown to represent a meaningful subgroup within the ADHD case base. The incorrectly classified ADHD subjects demonstrated a significantly decreased benefit from medication, as measured by improvements in saccade performance, when compared to correctly classified subjects. The ability of the CBR system to identify meaningful ADHD subgroups supports its potential use as a diagnostic tool by contributing to a multi-source diagnostic battery when coupled with other objective tests.
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Brien, D.C., Glasgow, J.I., Munoz, D.P. (2010). A Systematic Approach to the Design of a Case-Based Reasoning System for Attention-Deficit Hyperactivity Disorder. In: Jain, L.C., Lim, C.P. (eds) Handbook on Decision Making. Intelligent Systems Reference Library, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13639-9_19
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