Psychiatry

Functional near-infrared spectroscopy-based computer-aided diagnosis of major depressive disorder using explainable artificial intelligence: Comparison with conventional machine learning.

BACKGROUND AND OBJECTIVE: Only a limited number of explainable artificial intelligence (XAI) models have been developed for the functional near-infrared spectroscopy (fNIRS)-based computer-aided diagnosis (CAD) of major depressive disorder (MDD). In this study, we implemented an XAI model based on a convolutional neural network (CNN) specifically designed to highlight the differences in interhemis...

Artificial Intelligence in Mental Health: Promises and Perils.

The artificial intelligence (AI) revolution has already begun. AI scribes are charting. Chatbots are offering limited psychotherapy services. Researchers are trying to use AI to improve suicide risk prediction, psychiatric diagnosis, medication management, and health professional education. However, this technology is not without its faults. Human oversight and continued research remain crucial.

Research protocol for BootStRaP assessment phase: A nine-nation study on boosting societal adaptation and mental health in a rapidly digitalising, post-pandemic Europe.

BACKGROUND: There is increasing global concern about the harms associated with problematic usage of the internet (PUI) affecting young people. Various...

Drug grouping learning for improving evidence-based treatment recommendations.

Clinical practice guidelines (CPGs) are essential tools that facilitate the translation of the growing body of scientific evidence into clinical pract...

Self-Disclosure of Mental Health via Deepfakes: Testing the Effects of Self-Deepfakes on Affective Resistance and Intention to Seek Mental Health Support.

This study examines the use of deepfakes in self-disclosure interventions within mental health contexts. Specifically, we investigate how videos featu...

Integrating AI-driven technologies and facial-semantic features for depression detection: A cross-sectional study.

BACKGROUND: Depression is a major global health concern, still individuals with depressive tendencies remain undetected in outpatient settings due to ...

Disease and state dependent neural markers in adolescents with BD. Understanding the neural bases of mania, depression and remission in a data fusion approach.

BACKGROUND: Pediatric bipolar disorder (PBD) is a severe and disabling condition marked by alternating episodes of mania and depression, intermitted w...

Differential factor effects in comorbid depressive and anxiety symptoms (CDAS): A machine learning approach to individualized mental health promotion.

BACKGROUND: Depression and anxiety comorbid presents greater severity than isolated symptoms. Traditional analyses often fail to capture complex inter...

The scope of cardiology research: More than 300 topics covered through bibliometric evaluation.

This study provides a bibliometric overview of cardiovascular-related bibliometric research identified in the Scopus database using a title-abstract-k...

Digital phenotyping of depression: A multi-modal passive sensing approach to identifying novel behavioral and physiological markers of treatment response.

BACKGROUND: Despite advances in treatment approaches for Major Depressive Disorder (MDD), significant challenges persist in predicting individual trea...

Development of a machine learning model to predict the expanded disability status scale in multiple sclerosis patients.

OBJECTIVE: The assessment of disability in multiple sclerosis (MS) patients is crucial for treatment decisions and prognosis estimation. The Expanded ...

Artificial Intelligence: Promises and Perils for Employer-Sponsored Mental Health and Well-Being Initiatives.

Artificial intelligence (AI) is reshaping employer-sponsored mental health and well-being initiatives, offering new opportunities for personalized sup...

Machine learning analysis of clinical, psychological and sociodemographic factors predicting mental well-being in patients with severe mental illness: Insights from the French REHABase cohort.

PURPOSE: Mental well-being is a cornerstone of recovery for people with mental disorders. Unfortunately, despite many studies on the topic, the litera...

An explainable predictive machine learning model reveals ARRB2 as a key gene in post-traumatic stress disorder: A GEO database study.

A number of processes and pathways have been reported in the development of Post-Traumatic Stress Disorder (PTSD), however, novel biomarkers need to b...

Leveraging low-cost app-based step count data to assess depression and anxiety in university students: A cross-sectional mobile health study.

BACKGROUND: The prevalence of depression and anxiety among college students worldwide is on the rise, significantly impacting their health and quality...

The Influence of Sport Representation and Attitudes Toward Strength Training on Neuromuscular Performance Profiles in University Athletes: Part II Male Athletes.

McClean, ZJ, da Silva Torres, R, Herzog, W, Pasanen, K, Lun, V, and Jordan, MJ. The influence of sport representation and attitudes toward strength tr...

Urinary steroid metabolome shows adrenal, gonadal, and neuroactive steroid dysregulation in adolescents with depressive symptoms.

BACKGROUND: Steroid hormone profiles in affective disorders suggest hypothalamic-pituitary-adrenal (HPA) axis dysregulation and may reveal novel thera...

Adaptive network based fuzzy inference system efficientnet for autism spectrum disorder detection with optimization based pivotal region extraction.

Autism Spectrum Disorder (ASD) refers to abnormal neural activity that may increase the risk of premature brain development issues. Many traditional t...

Analysis of language patterns in schizophrenia based on natural language processing.

BACKGROUND: Schizophrenia is a severe mental disorder, with language dysfunction being one of its prominent features. Studies have shown that language...

Illustrating a framework for assessing generative artificial intelligence-based conversational agents for mental health.

BACKGROUND: Generative Artificial Intelligence (AI)-based conversational agents (CAs) hold promise for expanding mental health care access. AIMS: This...