About this Research Topic
Generative Artificial Intelligence (AI) has an unquestionable influence on the progress of scientific knowledge in psychosocial health, especially in the detection and prevention of common as well as less prevalent health disorders. AI systems are being used to improve the psychosocial well-being of patients with psychologically damaging diseases such as cancer, as they allow for a less invasive approach and improve their prognosis. AI also plays a major role in the field of health interventions. Algorithms created from messages posted on social networks help predict the risk of users suffering from mental health problems or psychopathology.
Generative AI also facilitates the inclusion of patients with functional diversity by creating universal communication channels and cognitive stimulation programs, thereby helping to create more humane and friendly environments. Furthermore, they offer the possibility of health education, facilitating adherence to treatment, and making training more accessible to health professionals. This enables them to acquire complex knowledge and train in simulated environments. Since generative AI contains highly sensitive personal information, it is necessary to publish protocols and measures that guarantee security in the handling of this information.
This Research Topic aims to provide valuable insights for health professionals, health managers, and other stakeholders, seeking to enhance the quality of life of people by showcasing practical examples and compiling interdisciplinary evidence on the effective integration of AI into health interventions. advances in mental and social health, which are facilitated by the use of generative AI. This includes the use of AI in prevention, diagnosis, intervention, and rehabilitation.
Some main topics of interest are:
Ways in which AI can be used in research on mental health
The use of AI to improve the learning methods of healthcare professionals.
The use of AI in decision-making in mental health
AI as a tool for predicting adverse effects of treatments
AI as a tool to increase patient adherence, as well as to support, accompany and monitor treatments.
The use of AI as a tool to make navigating mental health more accessible and inclusive through humanisation
Ways in which mental health professionals and policies secure sensitive information utilised by AI
Generative AI also facilitates the inclusion of patients with functional diversity by creating universal communication channels and cognitive stimulation programs, thereby helping to create more humane and friendly environments. Furthermore, they offer the possibility of health education, facilitating adherence to treatment, and making training more accessible to health professionals. This enables them to acquire complex knowledge and train in simulated environments. Since generative AI contains highly sensitive personal information, it is necessary to publish protocols and measures that guarantee security in the handling of this information.
This Research Topic aims to provide valuable insights for health professionals, health managers, and other stakeholders, seeking to enhance the quality of life of people by showcasing practical examples and compiling interdisciplinary evidence on the effective integration of AI into health interventions. advances in mental and social health, which are facilitated by the use of generative AI. This includes the use of AI in prevention, diagnosis, intervention, and rehabilitation.
Some main topics of interest are:
Ways in which AI can be used in research on mental health
The use of AI to improve the learning methods of healthcare professionals.
The use of AI in decision-making in mental health
AI as a tool for predicting adverse effects of treatments
AI as a tool to increase patient adherence, as well as to support, accompany and monitor treatments.
The use of AI as a tool to make navigating mental health more accessible and inclusive through humanisation
Ways in which mental health professionals and policies secure sensitive information utilised by AI
Keywords: Digital health technologies, e-inclusion, health, well-being, digital divide, artificial intelligence
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.
