ADHD/ADD

Automated AI-Based Aortic Measurements From Attenuation Correction CT as an Adjunctive Cardiovascular Risk Biomarker: An International Multicenter Study.

BACKGROUND: Aortic enlargement is a powerful predictor of dissection and rupture, yet it is rarely evaluated during routine myocardial perfusion imaging, despite the widespread availability of computed tomography (CT) attenuation correction scans. The aim of this study was to determine whether fully automated, opportunistically derived, artificial intelligence-based aortic measurements from myocar...

An attention-infused deep convolutional paradigm for multi-label classification of thoracic pathologies in chest radiographs.

This research proposes an empirical benchmarking study of an attention-infused deep convolutional framework for multi-label thoracic pathology classification in chest radiographs, designed to emulate how radiologists selectively focus on suspicious regions. Existing CNN models process entire images uniformly, often missing fine-grained or subtle abnormalities that require localized visual emphasis...

Cognitive Process Models Reveal Meaningful Brain-Behavior Associations in the Adolescent Brain Cognitive Development Study Stop-signal Task.

Characterizing associations between individual differences in brain activity and behavior remains a primary challenge in functional neuroimaging resea...

Electrophysiological Correlates of Attention- and Reward-related Brain Activity in Cannabis Users: Stage II Preregistered Research Report of a Longitudinal Study.

Continued drug use is thought to affect neural networks involved in attention and reward processing, with increased attentional bias being granted to ...

STELLAR-CB: Synthetic Temporal LSTM for Livestock Activity Recognition-Cow Behaviour.

Precision livestock farming (PLF) leverages activity sensors to monitor behaviours like grazing, resting and walking, yet class imbalance in datasets ...

What AI Cannot Teach: An Epistemological Reconceptualisation of the Nurse Educator Role Based on an Analysis of Carper's Ways of Knowing.

The rapid integration of artificial intelligence into healthcare and education is transforming how nurses teach, learn and acquire knowledge. Despite ...

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 a...

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 wi...

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...

Integration of artificial intelligence applications in clinical pharmacy services: A scoping review.

PURPOSE: Artificial intelligence (AI) is increasingly being integrated into healthcare systems, offering new opportunities to enhance the safety, effi...

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...