A Machine Learning Approach to Assist the Diagnosis of Depression

Abstract

Depression is a disease that is gradually becoming a widespread disease. Though there are methods of diagnosing depression through physicians, some individuals are not aware of the fact that they are under depression themselves thus raising an important issue in the medical sector. This dissertation concerns itself on depression and implements a solution for the diagnosis of depression as a proof of concepts. The study examines various methods of diagnosing depression including traditional methods as well as existing ICT solutions and implements the proposed web application through the use of supervised machine learning techniques. The findings of this research depict that the method used will be beneficial for the diagnosis of depression.