Psychiatry

Assessment of PTSD in military personnel via machine learning based on physiological habituation in a virtual immersive environment.

Posttraumatic stress disorder (PTSD) is a complex mental health condition triggered by exposure to t...

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...

The Extent to Which Artificial Intelligence Can Help Fulfill Metastatic Breast Cancer Patient Healthcare Needs: A Mixed-Methods Study.

The Artificial Intelligence Patient Librarian (AIPL) was designed to meet the psychosocial and suppo...

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...

Psychiatric Genomics 2025: State of the Art and the Path Forward.

Psychiatric genetics has evolved from candidate-gene studies to whole-genome sequencing efforts. Wit...

The use of artificial intelligence in psychotherapy: development of intelligent therapeutic systems.

BACKGROUND: The increasing demand for psychotherapy and limited access to specialists underscore the...

Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Within precision psychiatry, there is a growing interest in normative models given their ability to ...

Large language models and psychiatry.

Integrating Generative Artificial Intelligence and Large Language Models (LLMs) such as GPT-4 is tra...

AI-Augmented Psychosocial Interventions: A Bibliometric Review and Implications for Nursing.

PURPOSE: To map out the current artificial intelligence (AI)-informed psychosocial interventions res...

Machine Learning-Aided Intelligent Monitoring of Multivariate miRNA Biomarkers Using Bipolar Self-powered Sensors.

Breast cancer has become the most prevalent form of cancer among women on a global scale. The early ...

Finding purpose: Integrated latent profile and machine learning analyses identify purpose in life as an important predictor of high-functioning recovery after alcohol treatment.

BACKGROUND: Recent investigations of recovery from alcohol use disorder (AUD) have distinguished sub...

The predictive role of sedentary behavior and physical activity on adolescent depressive symptoms: A machine learning approach.

OBJECTIVE: This study aims to investigate the predictive value of sedentary behavior and physical ac...

Interpretable modality-specific and interactive graph convolutional network on brain functional and structural connectomes.

Both brain functional connectivity (FC) and structural connectivity (SC) provide distinct neural mec...

Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: Using a graph neural network.

AIM: Social anxiety disorder (SAD) is a mental disorder that requires early detection and treatment....

Identifying periphery biomarkers of first-episode drug-naïve patients with schizophrenia using machine-learning-based strategies.

Schizophrenia is a complex mental disorder. Accurate diagnosis and classification of schizophrenia h...

Pharmacogenomics and response to lithium in bipolar disorder.

AIMS: The present review explores the existing evidence on pharmacogenomic tests for prediction of l...

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...