Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment

• Published in: Brain informatics Vol. 10; no. 1; p. 10
• Main Authors: Squires, Matthew, Tao, Xiaohui, Elangovan, Soman, Gururajan, Raj, Zhou, Xujuan, Acharya, U Rajendra, Li, Yuefeng
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023; Springer; Springer Nature B.V; SpringerOpen
• Subjects: Algorithms; Artificial Intelligence; Care and treatment; Clinical outcomes; Cognitive Psychology; Computation by Abstract Devices; Computer Science; Deep learning; Depression; Depression, Mental; Diagnosis; Empirical analysis; Evidence-based medicine; Health care; Health Informatics; Health services; Heterogeneity; Innovations; Machine learning; Mental depression; Mental disorders; Mental health; Mental health care; Neural networks; Neurosciences; New technology; Psychiatric services; Psychiatry; Review; Surveys; Treatment response prediction; Unsupervised learning; Australia; Deep learning; Depression; Neural networks; Psychiatry; Artificial intelligence; Treatment response prediction

Informatics paradigms for brain and mental health research have seen significant advances in recent years. These developments can largely be attributed to the emergence of new technologies such as machine learning, deep learning, and artificial intelligence. Data-driven methods have the potential to...