Challenges and Future Research Directions in Automated Detection of Mental Illness Using Machine Learning
Year: 2024
Type: article
Abstract: The financial burden and prevalence of mental health disorders have enhanced globally, especially after the pandemic. Mental illness patients, especially children, find it hard to cope with educational, personal, and societal growth. Most of the children cannot access the treatment. Artificial intelligence (AI) models are exploited to identify the characteristics of mental illness. In this review, the focus is mainly on cognitive and developmental disorders. These disorders are attention-deficit/hyperactivity disorder (ADHD), Posttraumatic stress disorder, Tourette syndrome, obsessive-compulsive disorder, anxiety, schizophrenia, and autism spectrum disorder (ASD). Future research directions and current challenges in developmental and mental disorders are discussed.In this study, recent advancements like explainability, uncertainty, hardware implementation, and deep learning strategies are also described.
Author: Sadiq Hussain
Institution: Dibrugarh University
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4402698939