Latest AI and machine learning research in depression for healthcare professionals.
The integration of chatbots into psychiatry introduces a novel approach to support clinical decision-making, but biases in their recommendations pose significant concerns. This study investigates potential biases in chatbot-generated recommendations for adjunctive therapy in difficult-to-treat depression, comparing these outputs with the Canadian Network for Mood and Anxiety Treatments (CANMAT) 20...
BACKGROUND: Conventional approaches for major depressive disorder (MDD) screening rely on two effective but subjective paradigms: self-rated scales and clinical interviews. Artificial intelligence (AI) can potentially contribute to psychiatry, especially through the use of objective data such as objective audiovisual signals.
Speech is a noninvasive digital phenotype that can offer valuable insights into mental health conditions, but it is often treated as a single modali...
Mental disorders including depression, anxiety, and other neurological disorders pose a significant global challenge, particularly among individuals...
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) continues to rise among middle-aged and elderly populations, affecting not only p...
College students are increasingly affected by stress, anxiety, and depression, yet face barriers to traditional mental health care. This study evalu...
The proliferation of Large Language Models (LLMs) and Intelligent Virtual Agents acting as psychotherapists presents significant opportunities for e...
Previous studies reported that opioids depress breathing by inhibiting respiratory neural networks in the brainstem. The effects of opioids on sensory...
Identifying likely placebo responders can help design more efficient clinical trials by stratifying participants, reducing sample size requirements, a...
Suicide remains one of the main preventable causes of death among active service members and veterans. Early detection and prediction are crucial in...
Multimodal Dataset Distillation (MDD) seeks to condense large-scale image-text datasets into compact surrogates while retaining their effectiveness ...
The PERMANENS European project addresses the global public health challenge of self-harm and suicide by developing a machine learning-based Clinical D...
The therapeutic working alliance is a critical predictor of psychotherapy success. Traditionally, working alliance assessment relies on questionnaires...
BACKGROUND: Depression associated with Chronic Obstructive Pulmonary Disease (COPD) is a detrimental complication that significantly impairs patients'...
Depression and anxiety are common comorbidities of stroke. Research has shown that about 30% of stroke survivors develop depression and about 20% deve...
BACKGROUND: This study aimed to determine whether handwriting patterns are altered in individuals experiencing depressive episodes. Additionally, we d...
BACKGROUND: Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to ...
IMPORTANCE: Perinatal depression (PND) affects 10-20% of pregnant women, with significant racial disparities in prevalence, screening, and treatment. ...
People of all demographics are impacted by mental illness, which has become a widespread and international health problem. Effective treatment and sup...
BACKGROUND: Depression serves as a prodromal symptom of dementia, and individuals with depression exhibit a significantly higher risk of developing de...