Psychiatry

Do Anthropomorphic Chatbots Increase Counseling Satisfaction and Reuse Intention? The Moderated Mediation of Social Rapport and Social Anxiety.

The growing demand for mental health services and artificial intelligence chatbots to replace human agents have led to increased attention to chatbot anthropomorphizing. This study explored the effect of anthropomorphism on counseling satisfaction and reuse intention for chatbot-led mental health counseling and the mediating role of social rapport in the relationship. This study also examined the ...

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 in practical settings. We investigated whether clinical features of disease course, biomarkers from complete blood count, and blood biochemical markers could accurately classify unipolar and bipolar depression using machine learning methods. This retr...

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...

A "Do No Harm" Novel Safety Checklist and Research Approach to Determine Whether to Launch an Artificial Intelligence-Based Medical Technology: Introducing the Biological-Psychological, Economic, and Social (BPES) Framework.

Given the impact artificial intelligence (AI)-based medical technologies (hardware devices, software programs, and mobile apps) can have on society, d...

Attention Deficit Hyperactivity Disorder Classification Based on Deep Learning.

Attention Deficit Hyperactivity Disorder (ADHD) is a type of mental health disorder that can be seen from children to adults and affects patients' nor...

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. ...

Artificial intelligence in adolescents mental health disorder diagnosis, prognosis, and treatment.

Decoding reappraisal and suppression from neural circuits: A combined supervised and unsupervised machine learning approach.

Emotion regulation is a core construct of mental health and deficits in emotion regulation abilities lead to psychological disorders. Reappraisal and ...

Detecting individuals with severe mental illness using artificial intelligence applied to magnetic resonance imaging.

BACKGROUND: Identifying individuals at risk for severe mental illness (SMI) is crucial for prevention and early intervention strategies. While MRI sho...

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...

Mental Stress Detection Using a Wearable In-Ear Plethysmography.

This study presents an ear-mounted photoplethysmography (PPG) system that is designed to detect mental stress. Mental stress is a prevalent condition ...

Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification.

The validity and reliability of diagnoses in psychiatry is a challenging topic in mental health. The current mental health categorization is based pri...

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...

Biopsychosocial effects and experience of use of robotic and virtual reality devices in neuromotor rehabilitation: A study protocol.

BACKGROUND: Robot-assisted therapy (RAT) and virtual reality (VR)-based neuromotor rehabilitation have shown promising evidence in terms of patient's ...

Automated detection of schizophrenia using deep learning: a review for the last decade.

Schizophrenia (SZ) is a devastating mental disorder that disrupts higher brain functions like thought, perception, etc., with a profound impact on the...

Developing an Implementation Model for ADHD Intervention in Community Clinics: Leveraging Artificial Intelligence and Digital Technology.

Implementation of behavior therapy for ADHD faces challenges in community settings. We describe development of a community-based implementation model ...

Deep Learning-Based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease.

The prognosis and treatment of patients suffering from Alzheimer's disease (AD) have been among the most important and challenging problems over the l...

Leveraging deep learning models to understand the daily experience of anxiety in teenagers over the course of a year.

INTRODUCTION: Anxiety disorders are a prevalent and severe problem that are often developed early in life and can disrupt the daily lives of affected ...

Artificial scaffolding: Augmenting social cognition by means of robot technology.

The concept of scaffolding refers to the support that the environment provides in the acquisition and consolidation of new abilities. Technological ad...

Android robot was beneficial for communication rehabilitation in a patient with schizophrenia comorbid with autism spectrum disorders.