AIMC Topic: Mental Disorders

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The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review.

JMIR mental health
BACKGROUND: Mental health disorders affect an estimated 1 in 8 individuals globally, yet traditional interventions often face barriers, such as limited accessibility, high costs, and persistent stigma. Recent advancements in generative artificial int...

γ neuromodulations: unraveling biomarkers for neurological and psychiatric disorders.

Military Medical Research
γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric disorders, particularly in regulating executive and cognitive functions. This review explores the latest neuromodulation techniques, focusing on the cri...

AI in Medical Questionnaires: Innovations, Diagnosis, and Implications.

Journal of medical Internet research
This systematic review aimed to explore the current applications, potential benefits, and issues of artificial intelligence (AI) in medical questionnaires, focusing on its role in 3 main functions: assessment, development, and prediction. The global ...

It is Time to Realize the Promise of the Digital Mental Health Transformation: Application for Population Mental Health.

Journal of medical Internet research
The past 25 years have seen the explosion of digital health care-from 1s and 0s initially serving most researchers for accomplishing their work, to the creation of smartphones, mHealth, and more recently artificial intelligence. The revolution for di...

Navigating the Maze of Social Media Disinformation on Psychiatric Illness and Charting Paths to Reliable Information for Mental Health Professionals: Observational Study of TikTok Videos.

Journal of medical Internet research
BACKGROUND: Disinformation on social media can seriously affect mental health by spreading false information, increasing anxiety, stress, and confusion in vulnerable individuals, as well as perpetuating stigma. This flood of misleading content can un...

How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis.

BMC psychology
INTRODUCTION: Artificial Intelligence (AI) has become part of our everyday lives and is also increasingly applied in psychosocial healthcare as it can enhance it, make it more accessible, and reduce barriers for help seeking. User behaviour and readi...

AI for mental health: clinician expectations and priorities in computational psychiatry.

BMC psychiatry
Mental disorders represent a major global health challenge, with an estimated lifetime prevalence approaching 30%. Despite the availability of effective treatments, access to mental health care remains inadequate. Computational psychiatry, leveraging...

Use of Artificial Intelligence in Adolescents' Mental Health Care: Systematic Scoping Review of Current Applications and Future Directions.

JMIR mental health
BACKGROUND: Given the increasing prevalence of mental health problems among adolescents, early intervention and appropriate management are needed to decrease mortality and morbidity. Artificial intelligence's (AI) potential contributions, although si...

A Comparison of Responses from Human Therapists and Large Language Model-Based Chatbots to Assess Therapeutic Communication: Mixed Methods Study.

JMIR mental health
BACKGROUND: Consumers are increasingly using large language model-based chatbots to seek mental health advice or intervention due to ease of access and limited availability of mental health professionals. However, their suitability and safety for men...

Ethical and social issues in prediction of risk of severe mental illness: a scoping review and thematic analysis.

BMC psychiatry
BACKGROUND: Over the last decade, there has been considerable development in precision psychiatry, especially in the development of novel prediction tools that can be used for early prediction of the risk of developing a severe mental disorder such a...