A Brief Review of Artificial Intelligence Applications and Algorithms for Psychiatric Disorders

• Main Authors: Guang-Di Liu, Yu-Chen Li, Wei Zhang, Le Zhang
• Format: Article
• Language: English
• Published: Elsevier 2020-04-01
• Series: Engineering
• Subjects: Artificial intelligence; Psychiatric disorders; Neuroimaging
• Online Access: http://www.sciencedirect.com/science/article/pii/S2095809919300657

A number of brain research projects have recently been carried out to study the etiology and mechanisms of psychiatric disorders. Although psychiatric disorders are part of the brain sciences, psychiatrists still diagnose them based on subjective experience rather than by gaining insights into the pathophysiology of the diseases. Therefore, it is urgent to have a clear understanding of the etiology and pathogenesis of major psychiatric diseases, which can help in the development of effective treatments and interventions. Artificial intelligence (AI)-based applications are being quickly developed for psychiatric research and diagnosis, but there is no systematic review that summarizes their applications. For this reason, this study briefly reviews three main brain observation techniques used to study psychiatric disorders—namely, magnetic resonance imaging (MRI), electroencephalography (EEG), and kinesics diagnoses—along with related AI applications and algorithms. Finally, we discuss the challenges, opportunities, and future study directions of AI-based applications.