Latest AI and machine learning research in depression for healthcare professionals.
BACKGROUND: Collection of multimodal data (video, audio, and text) can yield digital biomarkers relevant to mental health, fatigue, and cognition. However, the feasibility and signal characteristics in operational populations remain underexplored. OBJECTIVE: The objectives of this study were to (1) extract an evidence-based library of vision, speech, and language features; (2) assess the feasibili...
Population aging worldwide has intensified the need to understand how mental health in later life is shaped by both cultural norms and structural systems. The book Mental Health in Older People Across Cultures underscores the central role of culture in shaping expectations about independence, emotional expression, and family roles, particularly in the context of depression. In this commentary, we ...
BACKGROUND: Depression in Parkinson's disease (dPD) is common and heterogeneous, impairs quality of life, and may accelerate disease progression. Tool...
Artificial intelligence (AI)-powered assessment, with its ability to process multimodal data and support real-time evaluation, is transforming traditi...
Depression is a prevalent and disabling syndrome characterized by sustained sadness and/or anhedonia, as well as cognitive and physical symptoms. In P...
PURPOSE: Research is needed to understand racial and ethnic differences in symptoms of depression. Unfortunately, most studies examine these differenc...
BACKGROUND: Cognitive behavioural therapy (CBT) is an empirically-supported treatment for depression, although some patients respond well and others d...
BACKGROUND: Smartphones generate continuous behavioral signals such as mobility and activity patterns, offering scalable opportunities for monitoring ...
BACKGROUND: Anecdotal evidence suggests that an increasing number of people are turning to generative artificial intelligence (GenAI) tools or artific...
INTRODUCTION: Internet-delivered psychological treatments have been developed and tested in many trials and are also implemented. AREAS COVERED: The a...
BACKGROUND: Generative artificial intelligence (AI) chatbots have rapidly entered public use, including in contexts involving emotional support and me...
Objective biobehavioral markers for mental health conditions remain elusive, with diagnosis typically relying on self-reports and clinical interviews....
Early depression detection is a critical task in public health, making automatic depression identification increasingly important. Existing multimodal...
BACKGROUND: Identifying patients with first-episode psychosis (FEP) at high mortality risk may facilitate personalized treatment regimen development a...
Adolescent suicide is a growing public health crisis, particularly in South Korea, which has one of the highest youth suicide rates among Organization...
OBJECTIVES: Suicide risk assessments currently rely on subjective clinical judgement, lacking objective measures. This study aimed to evaluate the ass...
BACKGROUND: Apathy, depression and anhedonia are clinically overlapping constructs, which hinders diagnostic clarity and treatment development. This s...
Cardiovascular disease represents the leading cause of mortality in China, accounting for over 40% of all deaths. Existing risk prediction models pred...
BACKGROUND: Depression as a mental illness is commonly observed to co-occur with various somatic diseases, such as gastrointestinal diseases. However,...
UNLABELLED: Major depressive disorder (MDD), a prevalent mental illness, currently lacks reliable biomarkers and depends predominantly on subjective d...