Psychiatry

Clinician Suicide Risk Assessment for Prediction of Suicide Attempt in a Large Health Care System.

IMPORTANCE: Clinical practice guidelines recommend suicide risk screening and assessment across behavioral health settings. The predictive accuracy of real-world clinician assessments for stratifying patients by risk of future suicidal behavior, however, remains understudied.

The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality.

The expanding domain of digital mental health is transitioning beyond traditional telehealth to incorporate smartphone apps, virtual reality, and generative artificial intelligence, including large language models. While industry setbacks and methodological critiques have highlighted gaps in evidence and challenges in scaling these technologies, emerging solutions rooted in co-design, rigorous eva...

[Health Equity in Mental Health Care: Challenges for Nurses and Related Preparation].

Individuals with mental illness face significant challenges in achieving health equity due to social and structural determinants, fragmented healthcar...

Differentiating Treatment-Resistant Depression With and Without Parkinsonism in the Elderly From a Psychiatric Perspective by Tc-TRODAT-1 SPECT Imaging.

OBJECTIVES: Late-life depression often overlaps with neurodegenerative diseases leading to diagnostic and treatment challenges for neuropsychiatrists....

Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.

Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to i...

Do Transformers and CNNs Learn Different Concepts of Brain Age?

"Predicted brain age" refers to a biomarker of structural brain health derived from machine learning analysis of T1-weighted brain magnetic resonance ...

Gray Matter Differences in Adolescent Psychiatric Inpatients: A Machine Learning Study of Bipolar Disorder and Other Psychopathologies.

BACKGROUND: Bipolar disorder (BD) is among the psychiatric disorders most prone to misdiagnosis, with both false positives and false negatives resulti...

Predicting Stress, Anxiety, and Depression in Adult Men Based on Nutritional and Lifestyle Variables: A Comparative Analysis of Machine Learning Methods.

Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these condition...

[EVALUATION OF SCREENING FOR PTSD USING CONSORT AI RECOMMENDATIONS WITH A LARGE LANGUAGE MODEL].

Similar to major natural disasters and large-scale wars, the events of October 7th and the retaliatory Iron Swords war resulted in both direct and ind...

Stratifying Risk for Postpartum Depression at Time of Hospital Discharge.

OBJECTIVE: Postpartum depression (PPD) is a major contributor to postpartum morbidity and mortality. Beyond efforts at routine screening, risk stratif...

HEDL: Deep learning multiple approaches for early detection of depression using sarcastic text.

Sarcasm is particularly notorious towards mental health, and thus it is quite essential for early identification of depressive indicators. This paper ...

Effect of Cumulative Exposure on the Efficacy of Paroxetine: A Population Pharmacokinetic-Pharmacodynamic and Machine Learning Analyses.

Selective serotonin reuptake inhibitors (SSRIs) are widely used in depression treatment. However, the relationship between treatment efficacy and plas...

Links between self-monitoring data collected through smartphones and smartwatches and the individual disease trajectories of adult patients with depressive disorders: Study protocol of a one-year observational trial.

Depression is highly recurrent and heterogenous in its individual course, requiring a personalized treatment approach. Patients today can collect larg...

An approach to screen susceptible rats and efficacy of an antidepressive treatment after chronic stress.

Chronic stress during life has been considered a risk factor for the development of psychiatric illness in humans. Chronic unpredictable stress batter...

Exploring the link between grandmaternal air pollution exposure and Grandchild's ASD risk: A multigenerational population-based study in California.

BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increasing prevalence. While genetics play a strong causal role, amon...

Artificial intelligence driven mental health diagnosis based on physiological signals.

Mental health disorders like stress, anxiety, and depression are increasing rapidly these days. Diagnosis of mental health disorders is a matter of co...

Discovery of Shared Latent Nonlinear Effective Connectivity for EEG-Based Depression Detection.

Granger causality (GC) effective connectivity (EC) calculated from electroencephalogram (EEG) signals has been widely used in mental disorder detectio...

A Hierarchical Graph Convolutional Network With Infomax-Guided Graph Embedding for Population-Based ASD Detection.

Recently, functional magnetic resonance imaging (fMRI)-based brain networks have been shown to be an effective diagnostic tool with great potential fo...

On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook.

Computational approaches to predicting mental health conditions in social media have been substantially explored in the past years. Multiple reviews h...

Ai-Aun Chatbot: A Pilot Study on the Effectiveness of an Artificial Intelligence Intervention for Mental Health Among Thai Older Adults.

Mental health disorders are a significant concern for older adults. Technology has the potential to provide support and companionship, which may impro...