Evaluation of OCD-Spectrum Disorders Using Data Analytics and Visualization Techniques
R. Yamini, Drishti De and Chavi Garg
Mental or psychological disorders are a serious problem to be resolved as they affect emotional stability and security for both the person and the environment. Obsessive Compulsive Disorder (OCD) is a long-lasting psychological disorder in which a person has uncontrollable, reoccurring thoughts (obsessions), and behaviours (compulsions) that he or she feels the urge to repeat over and over. This disorder is also known to branch into its various subtypes called the OCD-spectrum disorders, which include hoarding, body dysmorphic disorder, trichotillomania, etc. Hence, this paper is aimed towards discovering common symptoms and trends as well as the cognitive pathways influenced by various factors that lead to these disorders. This survey investigates recent research efforts and conducts a comprehensive overview of the work on medical big data, especially as related to OCD, its subtypes and its repercussions. It focuses on the full cycles of data processing which includes OCD data pre-processing, data analytics tools and algorithms along with visualization techniques. It attempts to integrate statistical techniques with clinically certified medical diagnosis in order to characterize the several elements that contribute to the mental transformation that a person undergoes. The result of this survey is expected to illustrate the standard ways that could help us better understand what treatment might work for which kind of patient.