Psychiatry

The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization.

For depression diagnosis, traditional methods such as interviews and clinical scales have been widel...

Application of Hybrid DeepLearning Architectures for Identification of Individuals with Obsessive Compulsive Disorder Based on EEG Data.

Obsessive-compulsive disorder (OCD) is a highly common psychiatric disorder. The symptoms of this c...

Prediction of adverse events risk in patients with comorbid post-traumatic stress disorder and alcohol use disorder using electronic medical records by deep learning models.

BACKGROUND: Identifying co-occurring mental disorders and elevated risk is vital for optimization of...

Assessing prognosis in depression: comparing perspectives of AI models, mental health professionals and the general public.

BACKGROUND: Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare...

A machine learning model to predict the risk of depression in US adults with obstructive sleep apnea hypopnea syndrome: a cross-sectional study.

OBJECTIVE: Depression is very common and harmful in patients with obstructive sleep apnea hypopnea s...

Exploring White Matter Abnormalities in Young Children with Autism Spectrum Disorder: Integrating Multi-shell Diffusion Data and Machine Learning Analysis.

RATIONALE AND OBJECTIVES: This study employed tract-based spatial statistics (TBSS) to investigate a...

Seeing through a robot's eyes: A cross-sectional exploratory study in developing a robotic screening technology for autism.

The present exploratory cross-sectional case-control study sought to develop a reliable and scalable...

Easing the Burden on Caregivers- Applications of Artificial Intelligence for Physicians and Caregivers of Children with Cleft Lip and Palate.

ObjectiveMany caregivers of children with cleft lip and palate experience a high level of anxiety th...

Exploring the impact of human-robot interaction on workers' mental stress in collaborative assembly tasks.

Advances in robotics have contributed to the prevalence of human-robot collaboration (HRC). However,...

Editorial: Psychometrics in psychiatry 2022: anxiety and stress disorders.

Control list of high-priority chemicals based on 5-HT-RI functionality and the human health interference effects selective CNN-GRU deep learning model.

The antidepressant drug known as 5-HT reuptake inhibitor (5-HT-RI) was commonly detected in biologic...

A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has bee...

Development of depression detection algorithm using text scripts of routine psychiatric interview.

BACKGROUND: A psychiatric interview is one of the important procedures in diagnosing psychiatric dis...

ChatGPT is not ready yet for use in providing mental health assessment and interventions.

BACKGROUND: Psychiatry is a specialized field of medicine that focuses on the diagnosis, treatment, ...

Interpretable deep learning model for major depressive disorder assessment based on functional near-infrared spectroscopy.

BACKGROUND: Major depressive disorder (MDD) affects a substantial number of individuals worldwide. N...

The performance of bibliometric analyses in the health sciences.

A bibliometric analysis (BA) is a knowledge synthesis methodology aimed at quantitively summarizing ...

ChatGPT is still struggling to revolutionize mental health policy.

Classification of attention deficit hyperactivity disorder using machine learning on an EEG dataset.

The neurodevelopmental disorder, Attention Deficit Hyperactivity Disorder (ADHD), frequently affecti...

Reliability and validity of artificial intelligence-based innovative digital scale for the assessment of anxiety in children.

AIM: To assess the reliability and validity of an AI-based, innovative digital scale for the assessm...

Psychotherapy, artificial intelligence and adolescents: ethical aspects.

Artificial intelligence (AI) has rapidly advanced in various domains, including its application in p...

Causal factors in childhood and adolescence leading to anabolic-androgenic steroid use: A machine learning approach.

BACKGROUND: Prior research has demonstrated associations between anabolic-androgenic steroid (AAS) u...