Depression

NSSI-Net: A Multi-Concept GAN for Non-Suicidal Self-Injury Detection Using High-Dimensional EEG in a Semi-Supervised Framework.

Non-suicidal self-injury (NSSI) is a serious threat to the physical and mental health of adolescents...

Postpartum depression in Northeastern China: a cross-sectional study 6 weeks after giving birth.

INTRODUCTION: Postpartum depression (PPD) is a prevalent mental health issue that poses significant ...

Unveiling the invisible: How cutting-edge neuroimaging transforms adolescent depression diagnosis.

Yu 's study has advanced the understanding of the neural mechanisms underlying major depressive diso...

AI tool flags people at high risk of post-partum depression.

Automated Depression Detection from Text and Audio: A Systematic Review.

Depression is a prevalent mental health disorder that presents significant challenges for timely dia...

Subtyping first-episode psychosis based on longitudinal symptom trajectories using machine learning.

Clinical course after first episode psychosis (FEP) is heterogeneous. Subgrouping and predicting lon...

Exploring potential diagnostic markers and therapeutic targets for type 2 diabetes mellitus with major depressive disorder through bioinformatics and in vivo experiments.

Type 2 diabetes mellitus (T2DM) and Major depressive disorder (MDD) act as risk factors for each oth...

Nursing Students' Perceptions of AI-Driven Mental Health Support and Its Relationship with Anxiety, Depression, and Seeking Professional Psychological Help: Transitioning from Traditional Counseling to Digital Support.

: The integration of artificial intelligence (AI) into mental health care is reshaping psychological...

Incorporating AI Into Military Behavioral Health: A Narrative Review.

INTRODUCTION: Concerns regarding suicide rates and declining mental health among service members hig...

WavFace: A Multimodal Transformer-Based Model for Depression Screening.

Depression, a prevalent mental health disorder with severe health and economic consequences, can be ...

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

One of the areas where artificial intelligence (AI) technologies are used is the detection and diagn...

A depression detection approach leveraging transfer learning with single-channel EEG.

Major depressive disorder (MDD) is a widespread mental disorder that affects health. Many methods co...

Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach.

BACKGROUND: Perinatal depression and anxiety significantly impact maternal and infant health, potent...

Suicide risk prediction for Korean adolescents based on machine learning.

Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) ...

The role of artificial intelligence in the prediction, identification, diagnosis and treatment of perinatal depression and anxiety among women in LMICs: a systematic review protocol.

INTRODUCTION: Perinatal depression and anxiety (PDA) is associated with a high risk of maternal mort...

Therapeutic potential of enzymes, neurosteroids, and synthetic steroids in neurodegenerative disorders: A critical review.

Neurodegenerative disorders present a significant challenge to healthcare systems, mainly due to the...

Trade-offs between machine learning and deep learning for mental illness detection on social media.

Social media platforms provide valuable insights into mental health trends by capturing user-generat...

Specific expression and common potential therapeutic drugs in different brain regions of major depressive disorder patients: bioinformatics analysis.

Major depressive disorder (MDD) is a prevalent and debilitating mental health condition characterize...

Decoding vital variables in predicting different phases of suicide among young adults with childhood sexual abuse: a machine learning approach.

Young adults with childhood sexual abuse (CSA) are an especially vulnerable group to suicide. Suicid...

Comparing three neural networks to predict depression treatment outcomes in psychological therapies.

OBJECTIVE: Artificial neural networks have been used in various fields to solve classification and p...