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With the advent of digital approaches to mental health, modern artificial intelligence (AI) (machine learning in particular) is being used in the development of prediction, detection, and treatment solutions for mental health care. Although there has been considerable progress in digital health and the application of AI to physical health in general, the adoption of AI in mental health is relatively nascent. However, opportunities are emerging. For example, in terms of treatment, AI can be incorporated into digital interventions, particularly web and smartphone apps, to enhance user experience and optimise personalised mental health care. In terms of prediction and detection, modern streams of abundant data, whether they be from medical imaging or an individual’s interactions with digital technologies, mean that data-driven AI methods can be employed to gain mental health insights.

The goal of this Research Topic is to bring together some of the latest research applying artificial intelligence to the field of mental health, as well as behavioural health and mental wellbeing more generally. Given the still rather nascent stage of this intersection, this collection of articles should serve to further establish the possibilities of applying AI to mental health, some of which are mentioned as follows. The first type of potential advance concerns the employment of AI techniques in digital phenotyping research, including ambient sensor/intelligence possibilities beyond smartphones and personal devices. Given their applicability, machine learning techniques are being employed in a variety of mental health applications, including digital phenotyping, natural language processing and analyses of neuroimaging. However, what applications are there of non-machine learning or symbolic AI approaches to the field of mental health, including expert systems. Furthermore, beyond research into such technologies, how are AI solutions to be integrated into and augment the practice of psychiatry or clinical psychology. Finally, there is also a need to address ethical and human-computer interaction dimensions of applying AI in mental health care.

We welcome papers concerning the application of artificial intelligence to mental health, as well as the related themes of behavioural health and mental wellbeing more generally. Types of manuscripts we are interested in are original research articles, reviews, opinion/perspective pieces, conceptual analyses, reports and clinical trials. Topics we are interested in include:

- Digital phenotyping from personal digital devices and the Internet of Things.
- Natural language processing of clinical texts and social media content.
- Chatbots and other AI agents for mental health.
- Expert systems for psychiatry.
- Applications of AI to neuroimaging or brain imaging.
- Ethics in the use of AI for mental health.
- Human-Computer Interaction aspects of AI-driven mental health tools.
- Clinical integration of AI solutions. Augmented psychiatry/psychology.

Keywords: Artificial Intelligence, Machine Learning, Mental Health, Digital Health, mHealth


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

With the advent of digital approaches to mental health, modern artificial intelligence (AI) (machine learning in particular) is being used in the development of prediction, detection, and treatment solutions for mental health care. Although there has been considerable progress in digital health and the application of AI to physical health in general, the adoption of AI in mental health is relatively nascent. However, opportunities are emerging. For example, in terms of treatment, AI can be incorporated into digital interventions, particularly web and smartphone apps, to enhance user experience and optimise personalised mental health care. In terms of prediction and detection, modern streams of abundant data, whether they be from medical imaging or an individual’s interactions with digital technologies, mean that data-driven AI methods can be employed to gain mental health insights.

The goal of this Research Topic is to bring together some of the latest research applying artificial intelligence to the field of mental health, as well as behavioural health and mental wellbeing more generally. Given the still rather nascent stage of this intersection, this collection of articles should serve to further establish the possibilities of applying AI to mental health, some of which are mentioned as follows. The first type of potential advance concerns the employment of AI techniques in digital phenotyping research, including ambient sensor/intelligence possibilities beyond smartphones and personal devices. Given their applicability, machine learning techniques are being employed in a variety of mental health applications, including digital phenotyping, natural language processing and analyses of neuroimaging. However, what applications are there of non-machine learning or symbolic AI approaches to the field of mental health, including expert systems. Furthermore, beyond research into such technologies, how are AI solutions to be integrated into and augment the practice of psychiatry or clinical psychology. Finally, there is also a need to address ethical and human-computer interaction dimensions of applying AI in mental health care.

We welcome papers concerning the application of artificial intelligence to mental health, as well as the related themes of behavioural health and mental wellbeing more generally. Types of manuscripts we are interested in are original research articles, reviews, opinion/perspective pieces, conceptual analyses, reports and clinical trials. Topics we are interested in include:

- Digital phenotyping from personal digital devices and the Internet of Things.
- Natural language processing of clinical texts and social media content.
- Chatbots and other AI agents for mental health.
- Expert systems for psychiatry.
- Applications of AI to neuroimaging or brain imaging.
- Ethics in the use of AI for mental health.
- Human-Computer Interaction aspects of AI-driven mental health tools.
- Clinical integration of AI solutions. Augmented psychiatry/psychology.

Keywords: Artificial Intelligence, Machine Learning, Mental Health, Digital Health, mHealth


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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