Psychiatry

Novel bayesian nonparametric unsupervised learning approach to precision symptom management in cancer survivors: a re-analysis of a comparative effectiveness trial.

Cancer survivors often experience multiple cooccurring symptoms such as insomnia, pain, fatigue, and anxiety; yet conventional analyses in symptom science typically analyze symptoms one at a time and thus overlook putative clusters of shared symptom experiences. We applied a novel machine learning approach to supporting tailored symptom management to cooccurring symptoms. Bayesian nonparametric (B...

Prediction of 12-Week Remission in Patients With Depressive Disorder Using Reasoning-Based Large Language Models: Model Development and Validation Study.

BACKGROUND: Depressive disorder affects over 300 million people globally, with only 30% to 40% of patients achieving remission with initial antidepressant monotherapy. This low response rate highlights the critical need for digital mental health tools that can identify treatment response early in the clinical pathway. OBJECTIVE: This study aimed to evaluate whether reasoning-based large language m...

Expression of Concern: Data Mining-Based Model for Computer-Aided Diagnosis of Autism and Gelotophobia: Mixed Methods Deep Learning Approach.

Triaging Casual From Critical-Leveraging Machine Learning to Detect Self-Harm and Suicide Risks for Youth on Social Media: Algorithm Development and Validation Study.

BACKGROUND: This study aims to detect self-harm or suicide (SH-S) ideation language used by youth (aged 13-21 y) in their private Instagram (Meta) con...

Evaluation of the neurotrophic peptide mixture in pathogenetic therapy of patients with Parkinson's disease.

This exploratory, single-group, open-label study investigated 17 patients with Parkinson's disease (PD) using a pre-post design. Motor and non-motor o...

Age matters: a narrative review and machine learning analysis on shared and separate multidimensional risk domains for early and late onset suicidal behavior.

There is considerable heterogeneity among late-life suicide attempters who can present stark differences in their suicidal trajectories. This work pro...

A Multimodal Neuro-Demographic Signature for Immuno-Metabolic Depression.

BACKGROUND: The underlying neurobiology of a recently described immuno-metabolic depression (IMD) subtype of major depressive disorder (MDD), characte...

Osteoarthritis year in review 2025: Biomechanics.

OBJECTIVE: Biomechanical loading is a known contributor to osteoarthritis (OA) pathogenesis, and one of the few modifiable risk factors. Thus, researc...

Explainable AI framework for improved Thalassemia mental health classification and feature selection.

Mental health challenges in Thalassemia patients are often overlooked, despite their significant impact on quality of life. Traditional statistical an...

User experience and safety of generative AI-based mental health chatbots: Scoping review protocol.

INTRODUCTION: Mental health problems constitute a significant global health challenge due to their rising prevalence and substantial treatment gap. Di...

Explainable machine learning for mental health prediction from social media behavior: a nested cross-validation study with SHAP and LIME interpretability.

Social media behavior is a promising source of early indicators for psychological distress; however, predictive models often lack transparency, limiti...

AI in geriatric psychiatry: precision meets human experience.

Artificial intelligence (AI) and robotics are rapidly transforming geriatric psychiatry, offering powerful tools for early detection, personalized tre...

AI literacy and psychosocial factors shaping Chinese university students' attitudes and behavioral intentions toward generative AI use.

Syntactic complexity of written text as a structural linguistic marker of depressive symptoms.

BACKGROUND: Language analysis methods have been increasingly explored for the detection of depressive symptoms. However, current approaches have large...

Thinking about tomorrow: A population-based natural language processing analysis of young adults' hopes and worries for the future.

BACKGROUND: The recent declines in youth mental health highlight the need for research into the factors underlying distress and those that foster well...

Advances on the application of the Human Brainnetome Atlas in obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is a chronic psychiatric disorder characterized by persistent intrusive thoughts and repetitive behaviors, signifi...

The role of the kynurenine pathway in the pathophysiology of autism-like phenotype induced by maternal inflammation in male mice.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with core symptoms that may include deficits in communication, social challenges, and ...

Linking subjective experience of anxiety to brain function using natural language processing.

Research on anxiety focuses on clinically relevant behaviours and neurophysiological responses, particularly emphasizing recruitment of amygdala, insu...

AI-driven speech biomarkers for disease diagnosis and monitoring: a systematic review and meta-analysis.

OBJECTIVE: This study aims to comprehensively review the literature on the use of speech biomarkers in disease diagnosis and monitoring, focusing on r...

Is ChatGPT a reliable informant? Dermatologists review AI-generated answers to frequently asked questions about melanoma.

Dear Editor, In recent years, many individuals have turned to the Internet for health-related information, a phenomenon commonly referred to as "Dr. G...