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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10791/302
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| Title: | A Diagnostic Model for ADHD with WLD in Students Using Healthcare Analytics |
| Authors: | Mitchnick, Diane |
| Supervisor(s): | Kumar, Vivekanandan (Faculty of Science and Technology, School of Computing and Information Systems) |
| Examining Committee: | Fraser, Shawn (Faculty of General Studies, Faculty of Health Disciplines)
Kinshuk (University of North Texas, College of Information)
Law, Sandra (Office of the Provost and Vice President Academic) |
| Degree: | Master of Science, Information Systems (MScIS) |
| Department: | Faculty of Science and Technology |
| Keywords: | Attention Deficit Hyperactivity Disorder
Written Language Disorder
ADHD
WLD
healthcare analytics
behavioural and learning disorder analysis |
| Issue Date: | 31-Oct-2019 |
| Abstract: | Previous research has shown students that have Attention Deficit Hyperactivity Disorder (ADHD), a mental health disorder that displays excessive inattentive, impulsive, and hyperactive behavioural symptoms, have an increased risk of having Written Language Disorder (WLD), a learning disorder that displays written composition issues (multiple spelling, grammar and punctuation mistakes, sentences that lack cohesion and topic flow, and written assignment completion). The prevalence of WLD without ADHD or another mental health disorder is quite rare.
To measure the prevalence of ADHD and WLD in a student, this research created a computational 'artificial neural network (ANN)' model that combined the outcomes of common screening tools for ADHD with written performance tasks as a measure for WLD. A study based on this ANN shows that ADHD students have a high prevalence of WLD in comparison to typical (non-ADHD or control) students, demonstrating the link between ADHD and WLD. |
| Graduation Date: | Nov-2019 |
| URI: | http://hdl.handle.net/10791/302 |
| Appears in Collections: | Theses & Dissertations
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