Ensemble hybrid learning methods for automated depression detection

• Main Authors: Ansari, Luna, Ji, Shaoxiong, Chen, Qian, Cambria, Erik
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Feature Extraction; Depression
• Online Access: https://hdl.handle.net/10356/163180
• Institution: Nanyang Technological University

Changes in human lifestyle have led to an increase in the number of people suffering from depression over the past century. Although in recent years, rates of diagnosing mental illness have improved, many cases remain undetected. Automated detection methods can help identify depressed or individuals...