Psychiatry

Deep-Learning-Based Analysis Reveals a Social Behavior Deficit in Mice Exposed Prenatally to Nicotine.

Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments in deep learning algorithms enable us to assess the behavioral phenotypes of animal models without cognitive bias during manual analysis. In this study, we established prenatal nicotine exposure (PNE) mice and evaluated their behavioral phenotypes us...

Automated analysis of speech as a marker of sub-clinical psychotic experiences.

Automated speech analysis techniques, when combined with artificial intelligence and machine learning, show potential in capturing and predicting a wide range of psychosis symptoms, garnering attention from researchers. These techniques hold promise in predicting the transition to clinical psychosis from at-risk states, as well as relapse or treatment response in individuals with clinical-level ps...

Impaired perception of a partner's synchronizing behavior reduces positive attitude toward humanoid robot in schizophrenia patients.

As interpersonal synchrony plays a key role in building rapport, the perception of another agent's synchronizing behavior could be an important featur...

Conversational assessment using artificial intelligence is as clinically useful as depression scales and preferred by users.

BACKGROUND: Depression is prevalent, chronic, and burdensome. Due to limited screening access, depression often remains undiagnosed. Artificial intell...

A bipolar intuitionistic fuzzy decision-making model for selection of effective diagnosis method of tuberculosis.

OBJECTIVES: Tuberculosis (TB) is a contagious illness caused by Mycobacterium tuberculosis. The initial symptoms of TB are similar to other respirator...

Health Care Professionals' Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis.

BACKGROUND: Mental health difficulties are highly prevalent worldwide. Passive sensing technologies and applied artificial intelligence (AI) methods c...

A multinational study on the factors influencing university students' attitudes and usage of ChatGPT.

Artificial intelligence models, like ChatGPT, have the potential to revolutionize higher education when implemented properly. This study aimed to inve...

Multiple Classification of Brain MRI Autism Spectrum Disorder by Age and Gender Using Deep Learning.

The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into nov...

A deep learning quantification of patient specificity as a predictor of session attendance and treatment response to internet-enabled cognitive behavioural therapy for common mental health disorders.

BACKGROUND: Increasing an individual's ability to focus on concrete, specific detail, thus reducing the tendency toward overly broad, decontextualised...

Human Digital Twin in Industry 5.0: A Holistic Approach to Worker Safety and Well-Being through Advanced AI and Emotional Analytics.

This research introduces a conceptual framework designed to enhance worker safety and well-being in industrial environments, such as oil and gas const...

Leveraging natural language processing to study emotional coherence in psychotherapy.

The association between emotional experience and expression, known as emotional coherence, is considered important for individual functioning. Recent ...

Comment on published article "A chat about bipolar disorder".

To the Editor, we follow the topic "A chat about bipolar disorder ". According to the study's findings, ChatGPT proved its ability to deliver basic an...

ASD-GResTM: Deep Learning Framework for ASD classification using Gramian Angular Field.

Autism Spectrum Disorder (ASD) is a heterogeneous disorder in children, and the current clinical diagnosis is accomplished using behavioral, cognitive...

Recentering responsible and explainable artificial intelligence research on patients: implications in perinatal psychiatry.

In the setting of underdiagnosed and undertreated perinatal depression (PD), Artificial intelligence (AI) solutions are poised to help predict and tre...

Effectiveness of Robotic Intervention on Improving Social Development and Participation of Children with Autism Spectrum Disorder - A Randomised Controlled Trial.

Evidence-based robotic intervention programmes for children with autism spectrum disorder (ASD) have been limited. As yet, there is insufficient evide...

Deep learning-based osteochondritis dissecans detection in ultrasound images with humeral capitellum localization.

PURPOSE: Osteochondritis dissecans (OCD) of the humeral capitellum is a common cause of elbow disorders, particularly among young throwing athletes. C...

Global brain analysis of minor hallucinations in Parkinson's disease using EEG and MRI data.

INTRODUCTION: Visual hallucination is a prevalent psychiatric disorder characterized by the occurrence of false visual perceptions due to misinterpret...

Exploring the Potential of Artificial Intelligence in Adolescent Suicide Prevention: Current Applications, Challenges, and Future Directions.

ObjectiveThe global surge in adolescent suicide necessitates the development of innovative and efficacious preventive measures. Traditionally, various...

Effectiveness of animal-assisted therapy and pet-robot interventions in reducing depressive symptoms among older adults: A systematic review and meta-analysis.

BACKGROUND: Systematic reviews suggest that animal-assisted therapy (AAT) and pet-robot interventions (PRI) achieve a reduction in mental health varia...

Analysis of KangDuo-SR-1500 and KangDuo-SR-2000 robotic partial nephrectomy from an operative and ergonomic perspective: a prospective controlled study in porcine models.

The objective of this study is to explore the safety and effectiveness of two new models of KangDuo surgical robots for partial nephrectomy in porcine...