Depression

Altered resting-state brain activity in patients with major depression disorder and bipolar disorder: A regional homogeneity analysis.

BACKGROUND: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive...

Interpretable machine learning model for predicting depression in middle-aged and elderly Chinese arthritis patients: A nationwide prospective cohort study.

Prediction of postpartum depression in women: development and validation of multiple machine learning models.

BACKGROUND: Postpartum depression (PPD) is a significant public health issue. This study aimed to de...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, a...

Comparison of an AI Chatbot With a Nurse Hotline in Reducing Anxiety and Depression Levels in the General Population: Pilot Randomized Controlled Trial.

BACKGROUND: Artificial intelligence (AI) chatbots have been customized to deliver on-demand support ...

Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm.

OBJECTIVE: To explore the risk factors that affect adolescents' suicidal and self-injurious behavior...

Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.

OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patie...

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.

BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and ...

Real-time monitoring to predict depressive symptoms: study protocol.

INTRODUCTION: According to the World Health Organization, Depression is the fourth leading cause of ...

Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach.

Major depressive disorder (MDD) is associated with reduced heart rate variability (HRV), but its lin...

Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) involves molecular alterations and pathway dysregulation...

Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study.

BACKGROUND: Depression, characterized by persistent sadness and loss of interest in daily activities...

The role of senescence-related genes in major depressive disorder: insights from machine learning and single cell analysis.

BACKGROUND: Evidence indicates that patients with Major Depressive Disorder (MDD) exhibit a senescen...

Graphene-based FETs for advanced biocatalytic profiling: investigating heme peroxidase activity with machine learning insights.

Graphene-based field-effect transistors (GFETs) are rapidly gaining recognition as powerful tools fo...

Corrigendum to "A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly" [J. Affect. Disord. Volume 369, 15 January 2025, Pages 329-337].

Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.

Objective classification biomarkers that are developed using resting-state functional magnetic reson...

Optimizing depression detection in clinical doctor-patient interviews using a multi-instance learning framework.

In recent years, the number of people suffering from depression has gradually increased, and early d...

Validation of a machine learning model for indirect screening of suicidal ideation in the general population.

Suicide is among the leading causes of death worldwide and a concerning public health problem, accou...

Neurobiologically interpretable causal connectome for predicting young adult depression: A graph neural network study.

BACKGROUND: There is a surprising lack of neuroimaging studies of depression that not only identify ...

Development and validation of short-term, medium-term, and long-term suicide attempt prediction models based on a prospective cohort in Korea.

BACKGROUND: This study aimed to develop and validate prediction models for short-(3 months), medium-...

Machine learning based seizure classification and digital biosignal analysis of ECT seizures.

While artificial intelligence has received considerable attention in various medical fields, its app...