Obsessive-Compulsive Disorder (OCD) is a long-lasting mental sickness described by unwanted thinking and impulse to carry out frequent tasks. These compulsive thoughts and behaviour seriously disturb people and hamper everyday life. Anybody can experience OCD, with the common beginning age being 19 years. Fifty percent of OCD sufferers first experience sensations in their early adolescence or childhood. Psychotherapy (talk therapy) and medication make up the majority of OCD treatment. OCD cannot be avoided. However, early detection and treatment can lessen the disease’s symptoms and negative impact on life. The quality of life and functioning in social, academic, and occupational settings are frequently improved in OCD patients who receive proper care. This article provides a taxonomy of computational methods designed for different aspects of OCD and provides some distinguished approaches. These approaches mostly focuss on OCD detection, OCD treatment response analysis, and OCD severity detection. Further, this article aims to highlight the research gap that indicates machine learning and data analytics for the early detection of OCD using Oxidative stress biomarkers.