Latest AI and machine learning research in depression for healthcare professionals.
Prompt engineering has the potential to enhance large language models’ (LLM) ability to solve tasks ...
Steroid hormone profiles in affective disorders suggest hypothalamic– pituitary–adrenal (HPA) axis d...
The lack of understanding of how individuals communicate suicidal stress hinders global suicide inte...
Large language model (LLM)-assisted early warning system may help overcome existing barriers to time...
Major depressive disorder (MDD) is a leading cause of disability worldwide, yet treatment response t...
Suicide is a leading cause of death among adolescents (aged 12–18), yet predicting it remains a sign...
Artificial intelligence (AI) is increasingly leveraged in mental healthcare for early detection, mon...
Recent increases in the prevalence rates of anxiety, depression, and suicidal ideation, especially i...
Early detection of suicide risk in adolescents is crucial but faces challenges including stigma, rel...
Recently, there has been a surge in the number of mental health cases including paranoid schizophren...
Patients recently discharged from psychiatric hospitalization are at increased risk of intentional s...
Non-suicidal self-injury (NSSI) in adolescents represents a critical public health issue. While symp...
Depression and anxiety are widespread mental health disorders, yet their diagnosis remains challengi...
Conversational agents based on large language models (LLMs) have shown moderate efficacy in reducing...
Machine learning models have increasingly been used to identify predictors of treatment response in ...
Depression affects millions worldwide with both pharmacological and psychological therapies widely a...
Machine learning approaches pave a promising avenue to advance individual predictions about psychiat...
Loneliness is a major psychological challenge in older adulthood, contributing to increased risks of...
Repetitive transcranial magnetic stimulation (rTMS) is an established intervention for treatment-res...
Large language models (LLMs) are rapidly entering clinical care, yet their definitionally probabilis...
To leverage sleep foundation models trained on large datasets of polysomnography for neurological di...