Psychiatry

Depression

Latest AI and machine learning research in depression for healthcare professionals.

1,366 articles
Stay Ahead - Weekly Depression research updates
Subscribe
Browse Categories
Showing 883-903 of 1,366 articles
MT-RCAF: A Multi-Task Residual Cross Attention Framework for EEG-based emotion recognition and mood disorder detection.

BACKGROUND AND OBJECTIVE: Prolonged abnormal emotions can gradually evolve into mood disorders such ...

Blood immuno-metabolic biomarker signatures of depression and affective symptoms in young adults.

BACKGROUND: Depression is associated with alterations in immuno-metabolic biomarkers, but it remains...

Using machine learning approach to predict suicide ideation and suicide attempts among Chinese adolescents: A cross-sectional study.

BACKGROUND: Screening for suicide ideation and suicide attempts is crucial for adolescents, yet accu...

Evaluating the ability of artificial intelligence to predict suicide: A systematic review of reviews.

INTRODUCTION: Suicide remains a critical global public health issue, with approximately 800,000 deat...

Prediction of first attempt of suicide in early adolescence using machine learning.

BACKGROUND: Suicide is the second leading cause of death among early adolescents, yet the first onse...

Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data.

Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and ...

Prediction of remission of pharmacologically treated psychotic depression: A machine learning approach.

BACKGROUND: The combination of antidepressant and antipsychotic medication is an effective treatment...

Multimodal depression recognition and analysis: Facial expression and body posture changes via emotional stimuli.

BACKGROUND: Clinical studies have shown that facial expressions and body posture in depressed patien...

Prediction of Adolescent Suicide Attempt by Integrating Clinical, Neurocognitive and Geocoded Neighborhood Environment Data.

BACKGROUND AND HYPOTHESIS: Suicide attempt is a complex behavior influenced by a combination of fact...

Incorporating end-user perspectives into the development of a machine learning algorithm for first time perinatal depression prediction.

OBJECTIVE: Machine learning algorithms can advance clinical care, including identifying mental healt...

A Weight-Aware-Based Multisource Unsupervised Domain Adaptation Method for Human Motion Intention Recognition.

Accurate recognition of human motion intention (HMI) is beneficial for exoskeleton robots to improve...

Machine learning applications related to suicide in military and Veterans: A scoping literature review.

OBJECTIVE: Suicide remains one of the main preventable causes of death among service members and vet...

Prediction of post stroke depression with machine learning: A national multicenter cohort study.

OBJECTIVE: Post-stroke depression (PSD) is a common psychiatric complication following stroke, with ...

Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis.

Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessm...

Exploring artificial intelligence (AI) Chatbot usage behaviors and their association with mental health outcomes in Chinese university students.

Technology dependence has long been a critical public health issue, especially among young people. W...

Construction and verification of risk prediction model for suicidal attempts of mood disorder based on machine learning.

BACKGROUND: Mood disorders (MD) are closely related to suicide attempt (SA). Developing an effective...

Neuroimaging pattern interactions for suicide risk in depression captured by ensemble learning over transcriptome-defined parcellation.

BACKGROUND: For suicide in major depression disorder, it is urgent to seek for a reliable neuroimagi...

Predictive Performance of Machine Learning for Suicide in Adolescents: Systematic Review and Meta-Analysis.

BACKGROUND: In the context of escalating global mental health challenges, adolescent suicide has bec...

Browse Categories