Psychiatry

Voices of change: associations between vocal markers and symptoms of ADHD - Findings from the LIFE child study.

In the context of precision psychiatry, voice characteristics in psychiatric disorders have significant potential as diagnostic markers. However, most studies have focused on adults, resulting in a poor understanding of paediatric voice characteristics. The diagnosis of attention-deficit/hyperactivity disorder (ADHD) lacks objectivity and could potentially benefit from the inclusion of voice featu...

Effectiveness and Usability of Artificial Intelligence and/or Machine Learning Enabled Wrist and Ankle Wearables for Physiological and Behavioral Monitoring in Children and Adolescents With Autism Spectrum Disorder: A Systematic Review.

Using machine learning to identify the strongest personal, school, and family correlates of youth mental health and well-being.

Research has identified numerous personal, school, and family factors associated with youth mental health, yet it remains unclear which correlates bes...

Smartphone App Using Reinforcement Learning for Obesity: Single-Arm Feasibility Study.

BACKGROUND: While behavioral interventions remain an evidence-based treatment for obesity, they often require long durations and frequent sessions. To...

Facial Expression-Based Evaluation of the Emotion Estimation Software Kokoro Sensor in Healthy Individuals: Validation and Reliability Pilot Study.

BACKGROUND: In recent years, artificial intelligence (AI) systems have increasingly been used to assess emotional states in health care. AI offers a s...

Effects of a Semantically Irrelevant Virtual Reality Experience on Memory and Emotion After Watching a Traumatic Event: Randomized Controlled Experimental Study.

BACKGROUND: First responders, such as firefighters, experience significant mental health issues due to the high-stress nature of their work. Existing ...

Hypnosis reshapes multilevel stress response and enhances executive performance in stressed medical students.

Stress and anxiety impair executive function and degrade performance, yet rapid and scalable interventions remain limited. This controlled study teste...

Psychiatry in transition: an assessment in the context of societal change.

AIMS: To explore how global challenges such as climate change, artificial intelligence (AI), and migration intersect with generational change among ps...

Plasma neurotransmitter-related metabolite alterations in adolescent major depressive disorder with and without psychotic features.

BACKGROUND: Whether adolescent major depressive disorder (MDD) with psychotic features has a distinct peripheral metabolite signature remains uncertai...

Attention-Enhanced Temporal and Spatial Feature Extraction Network for ADHD Diagnosis based on fMRI.

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder, and accurate diagnosis is critical for ensuring timely int...

Understanding the Brain as a Mentalizing Machine with a Symbol Grounding Function.

Social creatures can infer the mental states of others. This cognitive ability, called mentalizing, can be considered a process of inferring others' h...

Applying machine-learning and deep-learning to predict depression from brain MRI and identify depression-related brain biology.

The accuracy of grey-matter predictors of depression has remained limited. In this study, brain-based predictors of major depressive disorder (MDD) we...

Artificial Intelligence and CT Neuroimaging in Dementia and Psychotic Disorders: A Viewpoint.

Psychotic disorders are marked by heterogeneity in symptoms and treatment response, yet efforts to develop clinically useful predictive models through...

Endometriosis pain index: development of a model to predict poor pain-related quality of life after endometriosis surgery through machine learning analysis of registry data.

Predictive tools are lacking for pain-related outcomes after endometriosis surgery. The objective of this study was to develop and validate a machine ...

Predictive machine learning algorithms for depression and anxiety disorders in six cancer types: a comprehensive multi-center population-based study.

OBJECTIVE: Machine learning (ML) has advanced predictive modeling in medical diagnosis and risk assessment through large clinical datasets, yet applic...

Breaking barriers in women's pelvic health: claims-based economic analysis and healthcare utilization of an AI care program compared to usual care.

AIM: To compare healthcare utilization and spending among women enrolled in an employer-sponsored, artificial intelligence (AI) structured pelvic care...

Exploration of the mental attention mechanisms in motor imagery-based EEG decoding.

BACKGROUND: Brain-Computer Interface (BCI) systems enable direct communication between the brain and external devices, with motor imagery (MI)-based B...

Effectiveness of transcranial direct current stimulation (tDCS) on attention and memory biases in individuals with post-traumatic stress disorder (PTSD): a randomized, single-blind, parallel-group study.

Based on neurocognitive models, the development and maintenance of post-traumatic stress disorder (PTSD) are correlated with cognitive biases, includi...

Automated Identification of Accessory Mental Foramen Using Cone-Beam Computed Tomography and Convolutional Neural Networks.

INTRODUCTION AND AIMS: To develop and evaluate a deep learning-based system for automatic detection of the accessory mental foramen (AMF) using cone-b...

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BACKGROUND AND AIM: Over recent decades, formal requirements for medical records have been strengthened, for example through patients' rights of acces...