Artificial intelligence (AI) holds transformative potential for the care of people with mental health illnesses. This Review explores key domains and emerging applications of AI in mental health, emphasizing the challenges that must be addressed to e...
BACKGROUND: Psychiatric disorders are diagnostically challenging and often rely on subjective clinical judgment, particularly in resource-limited settings. Large language models (LLMs) have demonstrated potential in supporting psychiatric diagnosis; ...
PURPOSE OF REVIEW: This review examines the role of artificial intelligence (AI) in psychiatry in the past 5 years across four domains: screening; outcome prediction; risk and relapse prediction; and psychotherapy.
BACKGROUND: As mental health challenges continue to rise globally, there is an increasing interest in the use of GPT models, such as ChatGPT, in mental health care. A few months after its release, tens of thousands of users interacted with GPT-based ...
Good mental health is crucial for well-being. Unfortunately, despite the advancements of automatic detection solutions in the mental health field, along with the existence of effective treatments, a large percentage of affected people receive no care...
Athletes face a higher risk of mental health disorders compared to the general population, and prior theoretical and empirical work suggests that personality traits and training-related factors may play important roles in shaping athletes' mental hea...
BACKGROUND: In recent years, artificial intelligence (AI) has driven the rapid development of AI mental health chatbots. Most current reviews investigated the effectiveness of rule-based or retrieval-based chatbots. To date, there is no comprehensive...
BACKGROUND: Many youth rely on direct-to-consumer generative artificial intelligence (GenAI) chatbots for mental health support, yet the quality of the psychotherapeutic capabilities of these chatbots is understudied.
Machine learning techniques earn higher accuracy and robustness in multimorbidity prediction at this moment in time. Among various forms of multimorbidity, complex multimorbidity, especially the intersection of cardiometabolic disorders and mental he...
BACKGROUND: Mental health care systems worldwide face critical challenges, including limited access, shortages of clinicians, and stigma-related barriers. In parallel, large language models (LLMs) have emerged as powerful tools capable of supporting ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.