Finding Behavioural and Imaging Biomarkers of Major Depressive Disorder (MDD) using Artificial Intelligence: A Review

Major Depressive Disorder (MDD) is a serious ailment in mental health and is a medical illness that has a debilitating impact on a person's ability to think effectively. According to the World Health Organization (WHO), depression is the leading cause of disability with crippling nearly 350 million people globally. Accurate diagnosis and effective timely treatment are often challenging due to lack of early detection often due to lack of awareness, lack of effective diagnosing tools and sometimes, even a lack of trained mental health care practitioners. With high rates of comorbidity of MDD with other psychological diseases, it becomes imperative to delve deeper into finding effective biomarkers to easily distinguish the disease and effectively manage it. A dearth in finding effective ways to manage the disease has resulted in a high number of suicidal deaths making suicide the second leading cause of death globally. Many experts believe that Artificially Intelligent (AI) systems can be leveraged to manage this disease at various stages like early detection, diagnoses and treatment thereby helping mental health practitioners treat it effectively. This review gives an insight to the non-medical community on the basic characteristics of depression and aims to highlight the current trends in using artificial intelligence for the benefit of effectively curing and managing the illness of Depression. We delve into reviewing the behavioral and imaging biomarkers that AI can help effectively identify to detect and manage depression within populations globally. 2020 IEEE.Scopu