ADHD/ADD

Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational Study.

BACKGROUND: Functional impairments associated with mental health conditions are on the rise. Predicting functional outcomes may improve the targeting of preventive interventions. While prognostic models have primarily focused on psychosis, early recognition services require a transdiagnostic approach. OBJECTIVE: This study aimed to predict global functioning within a 2-year follow-up using baselin...

A hybrid deep learning approach for winter wheat yield prediction: evidence from leveraging multi-source data.

Accurate district-level wheat yield forecasts are critical for food security planning, supply-chain management, and agricultural policy in India, the world's second-largest wheat producer. We benchmark nine model classes for this task on a 23-year (2001-2023) dataset of 275 districts across India's seven largest wheat-producing states, which together account for ∼95% of national production. The be...

Associations between anterior hypothalamic subunits and ADHD and autistic traits revealed by deep learning MRI segmentation.

The hypothalamus is a central regulator of neuroendocrine function and social behavior, yet its internal organization has remained difficult to examin...

Diagnosis of ADHD in children from EEG signals using amplitude modulation features.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children and accurate diagnosis of this disorde...

"More Kairos, Less Chronos": Sleep, circadian rhythms and the path to cardiovascular, neurological and metabolic protection.

Sleep supports cardiovascular, metabolic, neurologic, and psychological health. Beyond duration, circadian alignment is crucial because regular sleep,...

Cochrane Evaluation of (Semi-) Automated Review Methods (CESAR): Protocol for an adaptive platform study within reviews.

BACKGROUND: Artificial intelligence (AI) has the potential to improve the efficiency of evidence synthesis and reduce human error. However, robust met...

Machine learning-based early warning model for adolescent mental health risk using the p factor.

BACKGROUND: Accurate identification of adolescents at high mental health risk is essential for timely intervention and improved service delivery. The ...

Mortality Risk Prediction from Dense PICU Data from Patients with Suspected Infection: Data-Derived Physiological Trajectories Outperform Expert Assessments When Temporal Resolution Is High.

OBJECTIVE: Early identification of mortality risk in critically ill children with suspected infection remains challenging. Whether severity scores (SI...

Prenatal exposure to residential greenness and artificial light at night and neurodevelopmental outcomes in children aged 4-12 years: A retrospective cohort study in China.

BACKGROUND: Neurodevelopmental outcomes may be shaped by modifiable residential environmental exposures during pregnancy; however, in rapidly urbanizi...

Anna vs. Judith: A randomized comparison of AI-delivered psychodynamic and cognitive behavioral therapies for social anxiety disorder.

Artificial intelligence (AI) offers a potential solution to the scalability limits of internet-based psychological interventions. This randomized cont...

A customized AI-based machine learning model for evaluating participants' activities under a workshop setting.

Human action recognition (HAR) in the workshop-style environment poses unique challenges due to class imbalance, fused action boundaries, and context ...

LIAUNet: Rethinking the Application of Loss Information in Medical Image Segmentation.

In recent years, with the development of medical imaging and deep learning technologies, medical image segmentation has played a crucial role in assis...

ADHD medications and preadolescent brain structure: patterns of cortical attenuation from the ABCD study.

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in the U.S. Amphetamine (AMP), methylphenidate (MPH), a...

Fine-grained classroom behavior monitoring for students with special education needs: an audiovisual fusion approach to posture analysis.

A core challenge of inclusive education lies in the difficulty teachers face in effectively identifying and responding to the diverse behavioral manif...

Simulation-Enhanced Learning in Nuclear Medicine: Counterpoint.

Simulation-based education has become widely embedded in health professional training and is increasingly positioned as a solution to clinical placeme...

Prediction of treatment response and adverse events in pediatric ADHD treated with acupuncture combined with conventional treatment.

INTRODUCTION: To develop and externally validate machine learning (ML) models for predicting treatment response and adverse events in children with at...

Behavioral Inhibition Network Predicts Alcohol Use in Men and Stress in Women.

OBJECTIVE: Impulsivity, a complex construct linked to addictions, is often inconsistently assessed and conceptualized, making it difficult to effectiv...

Language network functional connectivity in infancy predicts developmental language trajectories.

Although developmental language delays affect approximately 10% of children in the general population, the neurodevelopmental mechanisms that support ...

How to quickly determine whether patients with chronic cough need corticosteroid treatment--construction of a predictive model for corticosteroid-responsive cough in chronic cough.

Patients with chronic cough need to undergo a wide range of tests and rely on empirical medication to determine the underlying cause. Corticosteroid-r...

Analysis of electroencephalogram microstates and spectral power in children and adolescents with attention deficit hyperactivity disorder.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a widely recognized neurodevelopmental disorder characterized by inattention, hyperactivity, and im...