Psychiatry

Acoustic and Natural Language Markers for Bipolar Disorder: A Pilot, mHealth Cross-Sectional Study.

BACKGROUND: Monitoring symptoms of bipolar disorder (BD) is a challenge faced by mental health services. Speech patterns are crucial in assessing the current experiences, emotions, and thought patterns of people with BD. Natural language processing (NLP) and acoustic signal processing may support ongoing BD assessment within a mobile health (mHealth) framework.

Mental health practitioners' perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study.

BACKGROUND: As mental health disorders continue to surge, exceeding the capacity of available therapeutic resources, the emergence of technologies enabled by artificial intelligence (AI) offers promising solutions for supporting and delivering patient care. However, there is limited research on mental health practitioners' understanding, familiarity, and adoption intentions regarding these AI tech...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Changes in drug use in the general population during the COVID-19 pandemic and their long-term consequences are not well understood. We employed natur...

Leveraging artificial intelligence in the prediction, diagnosis and treatment of depression and anxiety among perinatal women in low- and middle-income countries: a systematic review.

AIM: The adoption of artificial intelligence (AI) tools is gaining traction in maternal mental health (MMH) research. Despite its growing usage, littl...

Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosp...

Acoustic Features for Identifying Suicide Risk in Crisis Hotline Callers: Machine Learning Approach.

BACKGROUND: Crisis hotlines serve as a crucial avenue for the early identification of suicide risk, which is of paramount importance for suicide preve...

Classification of schizophrenia spectrum disorder using machine learning and functional connectivity: reconsidering the clinical application.

BACKGROUND: Early identification of Schizophrenia Spectrum Disorder (SSD) is crucial for effective intervention and prognosis improvement. Previous ne...

A method for predicting postpartum depression via an ensemble neural network model.

INTRODUCTION: Postpartum depression (PPD) has numerous adverse impacts on the families of new mothers and society at large. Early identification and i...

The differential diagnosis of autism spectrum disorder in adults.

INTRODUCTION: Diagnosing autism spectrum disorder (ASD) in adults is challenging due to its heterogeneity and symptom overlap with other conditions. M...

Longitudinal brain age in first-episode mania youth treated with lithium or quetiapine.

It is unclear if lithium and quetiapine have neuroprotective effects, especially in early stages of bipolar and schizoaffective disorders. Here, an ag...

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in m...

Perceived Racism, Brain Development, and Internalizing and Externalizing Symptoms: Findings From the ABCD Study.

OBJECTIVE: Racial discrimination drives health disparities among racial/ethnic minority youth, creating chronic stress that affects brain development ...

Managing Screen Time in the Age of AI: Supporting Healthier Habits for Teens From the Inpatient Setting.

Psychiatric symptoms such as depressed mood, feelings of worthlessness, and anxiety can be exacerbated in adolescents by online content that mirrors t...

Using machine learning to investigate the influence of the prenatal chemical exposome on neurodevelopment of young children.

Research investigating the prenatal chemical exposome and child neurodevelopment has typically focused on a limited number of chemical exposures and c...

Text-Based Depression Prediction on Social Media Using Machine Learning: Systematic Review and Meta-Analysis.

BACKGROUND: Depression affects more than 350 million people globally. Traditional diagnostic methods have limitations. Analyzing textual data from soc...

Extreme Weather, Vulnerable Populations, and Mental Health: The Timely Role of AI Interventions.

Environmental disasters are becoming increasingly frequent and severe, disproportionately impacting vulnerable populations who face compounded risks d...

Evaluation of Anthropometric Measurement Results and the Relationship Between Individual Identity and Geographic Belonging Through Artificial Neural Networks from a Mental Health Perspective.

BACKGROUND: Identity verification and geographical belonging are significant issues with mental health implications, particularly in forensic contexts...

Semantic signals in self-reference: The detection and prediction of depressive symptoms from the daily diary entries of a sample with major depressive disorder.

Individuals with major depressive disorder (MDD) experience fewer positive and more negative emotions and use fewer positive words to describe themsel...

Classification of schizophrenia based on RAnet-ET: resnet based attention network for eye-tracking.

There is a notable need of quantifiable and objective methods for the classification of schizophrenia. Patients with schizophrenia exhibit atypical ey...

Using fuzzy decision support to create a positive mental health environment for preschoolers.

The preschool period is a crucial time for behavioural and social-emotional development and the cultivation of mental well-being. Preschoolers may be ...