Paper Type
Complete
Abstract
The global mental health landscape is facing an escalating crisis, with approximately one billion individuals affected by mental disorders, a situation exacerbated by the COVID-19 pandemic. The scarcity of specialized mental health services and the widespread stigma impede access to treatment, particularly in low- and middle-income countries. Artificial Intelligence (AI) has emerged as a promising tool in the detection and treatment of mental disorders, facilitating the analysis of large volumes of data. This study reviewed the application of AI in mental health, examining the types of disorders addressed, the technologies employed, and ethical considerations. Despite advancements, AI continues to encounter significant technical challenges, including data analysis limitations, and behavioral challenges, such as patient discomfort and apprehension regarding AI integration in treatment. Evidence suggests that, while promising, AI outcomes necessitate more rigorous validation and precise measurement, as well as a broader range of methodological approaches in future studies.
Paper Number
TR-1667
Recommended Citation
Daou, Iohan Youssef; Mozuck, Adriana Aparecida Alves Ferreira; Manfron Matias, Luiz Augusto; Hino, Marcia Cassitas; and Tomasi Junior, Darci Luiz, "Application of Artificial Intelligence in Mental Health: Challenges and Advances in the Detection and Treatment of Mental Disorders" (2025). AMCIS 2025 Proceedings. 6.
https://aisel.aisnet.org/amcis2025/translated/translated/6
Application of Artificial Intelligence in Mental Health: Challenges and Advances in the Detection and Treatment of Mental Disorders
The global mental health landscape is facing an escalating crisis, with approximately one billion individuals affected by mental disorders, a situation exacerbated by the COVID-19 pandemic. The scarcity of specialized mental health services and the widespread stigma impede access to treatment, particularly in low- and middle-income countries. Artificial Intelligence (AI) has emerged as a promising tool in the detection and treatment of mental disorders, facilitating the analysis of large volumes of data. This study reviewed the application of AI in mental health, examining the types of disorders addressed, the technologies employed, and ethical considerations. Despite advancements, AI continues to encounter significant technical challenges, including data analysis limitations, and behavioral challenges, such as patient discomfort and apprehension regarding AI integration in treatment. Evidence suggests that, while promising, AI outcomes necessitate more rigorous validation and precise measurement, as well as a broader range of methodological approaches in future studies.
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