Psychiatry

Beyond clinical observations: a scoping review of AI-detectable observable cues in borderline personality disorder.

Borderline Personality Disorder (BPD), impacting approximately 2% of adults worldwide, presents a formidable challenge in psychiatric diagnostics. Often underdiagnosed or misdiagnosed, BPD is associated with high morbidity and mortality. This scoping review embarks on a comprehensive exploration of observable cues in BPD, encompassing language patterns, speech nuances, facial expressions, nonverba...

Limbic/paralimbic connection weakening in preschool autism-spectrum disorder based on diffusion basis spectrum imaging.

This study aims to investigate the value of basal ganglia and limbic/paralimbic networks alteration in identifying preschool children with ASD and normal controls using diffusion basis spectrum imaging (DBSI). DBSI data from 31 patients with ASD and 30 NC were collected in Hunan Children's Hospital. All data were imported into the post-processing server. The most discriminative features were extra...

Uncovering key predictive channels and clinical variables in the gamma band auditory steady-state response in early-stage psychosis: a longitudinal study.

OBJECTIVE: Psychotic disorders are characterised by abnormalities in the synchronisation of neuronal responses. A 40 Hz gamma band deficit during audi...

Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the...

Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networ...

AI-enabled clinical decision support tools for mental healthcare: A product review.

The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decision Support Systems (AI-CDSS) for mental healthcare...

Screening social anxiety with the Social Artificial Intelligence Picture System.

Social anxiety disorder (SAD) is a prevalent anxiety disorder marked by strong fear and avoidance of social scenarios. Early detection of SAD lays the...

Editorial: Improving autism spectrum disorder diagnosis using machine learning techniques.

A pilot evaluation of school-based LEGO® robotics therapy for autistic students.

There is emerging evidence that LEGO® therapy is an effective way of supporting younger autistic children develop their communication and social skill...

Using deep learning to classify developmental differences in reaching and placing movements in children with and without autism spectrum disorder.

Autism Spectrum Disorder (ASD) is among the most prevalent neurodevelopmental disorders, yet the current diagnostic procedures rely on behavioral anal...

Machine Learning-Based Suicide Risk Prediction Model for Suicidal Trajectory on Social Media Following Suicidal Mentions: Independent Algorithm Validation.

BACKGROUND: Previous efforts to apply machine learning-based natural language processing to longitudinally collected social media data have shown prom...

The analysis of generative adversarial network in sports education based on deep learning.

The importance of mental health is increasingly emphasized in modern society. The assessment of mental health qualities among college and university s...

Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by differences in social communication and repetitive behaviors, often ...

CALLM: Enhancing Clinical Interview Analysis Through Data Augmentation With Large Language Models.

The global prevalence of mental health disorders is increasing, leading to a significant economic burden estimated in trillions of dollars. In automat...

Understanding veterinary practitioners' responses to adverse events using a combined grounded theory and netnographic natural language processing approach.

Support that mitigates the detrimental impact of adverse events on human healthcare practitioners is underpinned by an understanding of their experien...

Research hotspots and trends of neuroimaging in social anxiety: a CiteSpace bibliometric analysis based on Web of Science and Scopus database.

BACKGROUND: This study focused on the research hotspots and development trends of the neuroimaging of social anxiety (SA) in the past 25 years.

Predictive utility of artificial intelligence on schizophrenia treatment outcomes: A systematic review and meta-analysis.

Identifying optimal treatment approaches for schizophrenia is challenging due to varying symptomatology and treatment responses. Artificial intelligen...

AI-based medication adherence prediction in patients with schizophrenia and attenuated psychotic disorders.

OBJECTIVE: The capacity of machine-learning algorithms to predict medication adherence was assessed using data from AiCure, a computer vision-assisted...

Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis us...

Training humans to supplement a machine learning system: The role of guides in a digital mental health intervention.

Machine learning (ML) is increasingly prevalent in mental health care, with contemporary initiatives leveraging these technologies, sometimes in combi...