Artificial Intelligence for Mental Health: A Review of AI Solutions and Their Future
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As an aftermath of the global COVID-19 outbreak, the importance for the attention of mental health disorders was brought back to the spotlight. Conditions such as anxiety and depression have been identified as leading causes of disability worldwide, being the latter a concern due to its effects, such as lower quality of life, or even suicidal ideation and execution. Despite this situation, healthcare systems around the world face difficulties to provide mental care to their inhabitants because of different challenges, such as not enough funding, lack of infrastructure, or trained personnel in some geographic areas. Thus, there exists a need to be fulfilled in the field of mental health attention. According to a literature review, artificial intelligence (AI) could provide mental health support in ways that were not possible before, with options such as being available anytime, through text, speech, or even with physical interfaces in the case of robots. However, among the general public, and as well in professional communities, there is not enough understanding of how does AI work. Therefore, in this chapter, we offer a brief introduction to AI and cognitive-behavioral therapy, a common therapeutic approach used in AI applications. Next, we discuss how AI manages to achieve mental health goals through different technologies, such as machine learning, detection of speech patterns, and computer vision, among others. Then, examples of AI in three different areas are presented, considering their attributes and how these may support mental health. Finally, ethical considerations of using AI for mental health are examined, addressing issues such as privacy, security, and accessibility that should be considered in the development of any project development in the field of AI for mental health. © 2024 selection and editorial matter, Manuel Cebral-Loureda, Elvira G. Rincón-Flores and Gildardo Sanchez-Ante.
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