Depression

Altered thalamic subregional connectivity with default mode and frontoparietal networks in adolescents with depression.

BACKGROUND: The thalamus plays a pivotal role in the pathophysiology of adolescent depression, with its subregions showing functional heterogeneity. Abnormalities in the default mode (DMN) and frontoparietal networks (FPN) are associated with depressive symptoms, and both networks are closely coupled with the thalamus. This study examined, at a finer granularity, functional connectivity (FC) chang...

Differential Effects of Prenatal Depression and Anxiety on Infant Sleep: Dual-Pathway Mechanisms Involving the HPA Axis and the Gut-Brain Axis.

STUDY OBJECTIVES: Prenatal psychological distress is associated with adverse offspring outcomes, including infant sleep disturbances and altered gut microbiota, yet the mediating roles of neonatal gut microbiome and tryptophan metabolism remain underexplored. METHODS: This prospective birth cohort study enrolled 2288 mother-infant pairs, using questionnaires to assess prenatal anxiety/depression a...

Interstitial lung disease pattern recognition on full high resolution computed tomography volume: Development and evaluation of a decision-support tool for less-experimented radiologists.

PURPOSE: The purpose of this study was to develop an artificial intelligence (AI) tool to assist recognition of three major interstitial lung disease ...

An interpretable predictive model for depression risk in diabetic patients: A web-based application using NHANES data.

Depression is a common comorbidity in individuals with diabetes and is associated with adverse clinical outcomes. Early identification of high-risk in...

Machine learning models to predict ICU admission of patients with COPD and depression: A retrospective cohort study.

This study aimed to develop and validate a machine learning (ML)-based predictive model to identify risk factors associated with intensive care unit (...

CastNet: A three-channel EEG-based deep learning model for cross-subject depression detection.

Depression is a serious mental health condition affecting millions worldwide. In recent years, deep learning models achieved remarkable performance in...

Tumor ablation: emerging uses, challenges, and strategic implementation. A green paper by the Network of Expertise in Cancer (JANE-2), High Tech Medical Resources, network on Physical Methods of Tumor Ablation.

The field of oncology has witnessed remarkable progress with the integration of high-tech innovations in tumor ablation. Tumor ablation therapies, suc...

Distinct and Shared Molecular Mechanisms Underlie Morphological-Functional Overcoupling and Undercoupling in Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) exhibits significant heterogeneity in alterations of brain morphology and function, however, the potential...

Novel genetic insights into causal effects of depression on non-alcoholic fatty liver diseases partially mediated by gut microbiota.

Depression and non-alcoholic fatty liver disease (NAFLD) are increasingly recognized as interconnected disorders, yet the causal mechanisms linking th...

Integrated remote sensing and aeromagnetic datasets for mapping iron mineralization potential in the El-Bahariya depression in the Western Desert of Egypt.

The El-Bahariya depression in the Western Desert of Egypt is well-known for its iron ore deposits, with mineralization recorded in five well-known loc...

Discrimination of generalized anxiety and major depressive disorders by machine learning of resting-state functional MRI.

OBJECTIVE: To address the clinical difficulty of differentiating Generalized Anxiety Disorder (GAD) from Major Depressive Disorder (MDD), this study a...

AI-driven tripartite classification for optimizing wearable bioelectronics in depression management.

Current disease-sensing devices primarily focus on distinguishing between healthy and diseased states, effective for diagnosis but limited in guiding ...

Circadian Rhythm Stabilization App to Prevent Mood Episode Recurrence in Patients With Mood Disorders: A Multicenter, Double-Blind, Sham-Controlled, Randomized Clinical Trial.

OBJECTIVE: Preventing recurrence is essential for improving the clinical course of major depressive disorder (MDD) and bipolar disorder (BD). The auth...

Enhancing Cognitive Functions of Older Adults With Software Robot: Longitudinal Exploratory Field Study.

BACKGROUND: The global prevalence of dementia continues to rise and demands scalable, nonpharmacological interventions. Digital cognitive training has...

Supporting Student Mental Health With the Safespace Generative AI Chatbot: Mixed Methods Feasibility Study.

BACKGROUND: Generative artificial intelligence (GenAI) chatbots have the potential to provide personalized mental health support to individuals at sca...

Leveraging simulation to provide a practical framework for estimating the novel scope of risk of large language models in healthcare.

BACKGROUND: Large language models (LLMs) are rapidly entering clinical and consumer use, yet their probabilistic outputs have delivered a variety of u...

Comprehensive analysis of interactions between brain aging and late-onset psychoses using heuristic mapping models.

BACKGROUND: Advanced brain aging is closely associated with late-onset psychoses, including bipolar disorder(BD), schizophrenia(SP), and major depress...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Harnessing artificial intelligence for suicidality detection.

A scoping review of the use of artificial intelligence as a psychological assessment tool.

Mental health disorders are highly prevalent worldwide, yet access to timely and effective mental health assessment (and care) remains limited. Artifi...