Exploratory Data Mining Techniques (Decision Tree Models) for Examining the Impact of Internet-Based Cognitive Behavioral Therapy for Tinnitus: Machine Learning Approach

Background: There is huge variability in the way that individuals with tinnitus respond to interventions. These experiential variations, together with a range of associated etiologies, contribute to tinnitus being a highly heterogeneous condition. Despite this heterogeneity, a “one size fits all” ap...

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Bibliographic Details
Published in:	Journal of medical Internet research 2021-11, Vol.23 (11), p.e28999
Main Authors:	Rodrigo, Hansapani, Beukes, Eldré W, Andersson, Gerhard, Manchaiah, Vinaya
Format:	Article
Language:	English
Subjects:	Algorithms Anxiety Artificial intelligence Behavior modification Classification Clinical outcomes Clinical research Clinical trials Cognition Cognitive behavioral therapy Cognitive functioning Cognitive style Cognitive-behavioral factors Data collection Data mining Decision analysis Decision trees Decisions Demographics Demography Disability Ears & hearing Education Educational attainment Ethics Hearing aids Hearing disorders Hearing loss Heterogeneity Higher education Information retrieval Insomnia Internet Intervention Learning outcomes Life satisfaction Machine learning Medical decision making Medical treatment Multimedia Original Paper Prediction models Predictions Psychotherapy Quality of life Questionnaires Regression analysis Satisfaction Self help Sound Tinnitus Variables
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