ADHD/ADD

Development of a Reliable and Valid DSM-5-Based ADHD Self-Report Scale for 8- and 9-Year-Old Children.

We examined the validity and reliability of the DSM-5-Based Childhood ADHD Self Report Scale (DSM-5-CASRS), a self-report questionnaire developed to assess Attention-Deficit/Hyperactivity Disorder (ADHD) symptoms in elementary school children. Two-hundred twelve elementary school second-grade children (130 children with ADHD and 82 non-ADHD) derived from an epidemiological sample completed our sca...

MeLSI: Metric Learning for Statistical Inference in microbiome community composition analysis.

Microbiome beta diversity analysis relies on distance-based methods, including permutational multivariate analysis of variance (PERMANOVA) combined with fixed ecological distance metrics (Bray-Curtis, Euclidean, Jaccard, and UniFrac), which treat all microbial taxa uniformly, regardless of their biological relevance to community differences. This "one-size-fits-all" approach may miss subtle but bi...

Echocardiographic assessment in arterial hypertension: a contemporary narrative review.

Arterial hypertension remains the leading modifiable cause of cardiovascular morbidity and mortality resulting in characteristic changes in cardiac st...

O-RADS for assessment of adnexal lesions: current status, challenges and future directions.

The Ovarian-Adnexal Reporting and Data System (O-RADS), developed by the American College of Radiology (ACR), provides a standardized, evidence-based ...

Tonotopically distinct OFF responses arise in the mouse auditory midbrain following sideband suppression.

The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these d...

AI-assisted Software Development in Digital Dentistry: A Technical Innovation Report with Three Open-Source Applications.

OBJECTIVES: To present a feasible workflow for artificial intelligence (AI)-assisted software engineering in dentistry as a technical innovation repor...

Prediction of all-cause mortality in older adults in Colombia: real-world evidence from a middle-income country.

Accurate mortality prediction in older adults is a critical component of precision public health and risk stratification in healthcare systems worldwi...

Patient and Facility Factors Associated with Uptake of NTAP-Billed AI to Identify Suspected LVO in Ischemic Stroke.

PURPOSE: Medicare's New Technology Add-On Payment (NTAP) incentivizes the adoption of innovative technologies. We examined factors associated with the...

Are patient-derived models of amyotrophic lateral sclerosis a game changer for novel drug discovery?

INTRODUCTION: ALS drug discovery has long depended on model systems that incompletely capture human disease heterogeneity, aging, and TDP-43 proteinop...

A fully inductive inference protocol for population GNNs in single-subject brain disorder diagnosis.

Population graph-based Graph Neural Networks (GNNs) have demonstrated superior performance in brain disease diagnosis by modeling inter-subject relati...

Data-Driven Profiles of Youth Executive Function and Their Longitudinal Associations With Externalizing Problems.

OBJECTIVE: Executive function (EF) deficits are observed in externalizing disorders. However, research has yet to explore the specificity of these ass...

Research on dynamic cost prediction method for power technology upgrading projects based on improved transformer neural network.

Accurate cost prediction is critical for the effective management of power grid technical renovation (PGTR) projects, yet conventional methods struggl...

Bayesian Uncertainty-aware Deep Learning with noisy labels: Tackling annotation ambiguity in EEG seizure detection.

Deep learning is advancing EEG processing for automated epileptic seizure detection and onset zone localization, yet its performance relies heavily on...

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 ...

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 ...

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 ...