Depression

ChatGPT on ECT: Can Large Language Models Support Psychoeducation?

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks de...

Machine Learning and Electroencephalogram Signal based Diagnosis of Dipression.

Depression is a psychological condition which hampers day to day activity (Thinking, Feeling or Action). The early detection of this illness will help...

Higher depression risks in medium- than in high-density urban form across Denmark.

Urban areas are associated with higher depression risks than rural areas. However, less is known about how different types of urban environments relat...

Development of deep learning model and evaluation in real clinical practice of lingual mandibular bone depression (Stafne cyst) on panoramic radiographs.

OBJECTIVES: Lingual mandibular bone depression (LMBD) is a developmental bony defect in the lingual aspect of the mandible that does not require any s...

Chronic Stress Exposure Alters the Gut Barrier: Sex-Specific Effects on Microbiota and Jejunum Tight Junctions.

BACKGROUND: Major depressive disorder (MDD) is the leading cause of disability worldwide. Of individuals with MDD, 30% to 50% are unresponsive to comm...

Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.

BACKGROUND: Previous studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COV...

Optimizing multi-domain hematologic biomarkers and clinical features for the differential diagnosis of unipolar depression and bipolar depression.

There is a lack of objective features for the differential diagnosis of unipolar and bipolar depression, especially those that are readily available i...

Applications of artificial intelligence-machine learning for detection of stress: a critical overview.

Psychological distress is a major contributor to human physiology and pathophysiology, and it has been linked to several conditions, such as auto-immu...

Machine Learning Algorithms Can Be Reliably Leveraged to Identify Patients at High Risk of Prolonged Postoperative Opioid Use Following Orthopedic Surgery: A Systematic Review.

Machine learning (ML) has emerged as a method to determine patient-specific risk for prolonged postoperative opioid use after orthopedic procedures. ...

Deep neural network for food image classification and nutrient identification: A systematic review.

Technology impacts human life in both the aspects such as positive and negative, which helps in better communication and eliminating geographical boun...

Automatic implant shape design for minimally invasive repair of pectus excavatum using deep learning and shape registration.

Minimally invasive repair of pectus excavatum (MIRPE) is an effective method for correcting pectus excavatum (PE), a congenital chest wall deformity c...

The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support.

The combination of artificial intelligence (AI) technology with the real economy has dramatically improved the efficiency of enterprises. However, the...

Evaluating of the clinical eff ect of the robocare nursing model in Da Vinci robot-assisted radical cancer surgery.

Predictors of suicide ideation among South Korean adolescents: A machine learning approach.

BACKGROUND: The current study developed a predictive model for suicide ideation among South Korean (Korean) adolescents using a comprehensive set of f...

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In ...

Effects of a cognitive-based intervention program using social robot PIO on cognitive function, depression, loneliness, and quality of life of older adults living alone.

OBJECTIVE: Social robot interventions are being implemented to reduce cognitive decline, depression, and loneliness among older adults. However, the t...

User Feedback on the Use of a Natural Language Processing Application to Screen for Suicide Risk in the Emergency Department.

Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the ability to predict who will die by suicide is sti...

Cognitive Depression Detection Cyber-Medical System Based on EEG Analysis and Deep Learning Approaches.

Long-term depression and negative emotional cycles affect life quality and work productivity. However, depression is not easy to detect, with current ...

Understanding and detecting behaviours prior to a suicide attempt: A mixed-methods study.

OBJECTIVE: Prior research suggests there are observable behaviours preceding suicide attempts in public places. However, there are currently no ways t...