AIMC Topic: Mental Disorders
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It is Time to Realize the Promise of the Digital Mental Health Transformation: Application for Population Mental Health.
Journal of medical Internet research
Jun 19, 2025
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
Jun 18, 2025
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
Jun 6, 2025
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
Jun 6, 2025
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
Jun 6, 2025
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
May 21, 2025
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
May 19, 2025
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...
A controlled trial examining large Language model conformity in psychiatric assessment using the Asch paradigm.
BMC psychiatry
May 12, 2025
BACKGROUND: Despite significant advances in AI-driven medical diagnostics, the integration of large language models (LLMs) into psychiatric practice presents unique challenges. While LLMs demonstrate high accuracy in controlled settings, their perfor...
The Applications of Large Language Models in Mental Health: Scoping Review.
Journal of medical Internet research
May 5, 2025
BACKGROUND: Mental health is emerging as an increasingly prevalent public issue globally. There is an urgent need in mental health for efficient detection methods, effective treatments, affordable privacy-focused health care solutions, and increased ...
Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 5, 2025
For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). In order to effectively identify the most significant biomarkers associated w...
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