ADHD/ADD

Unmasking data leakage in EEG-ADHD literature: a rigorous, interpretable SOTA framework (DSAEN).

The field of translational Electroencephalogram-Artificial Intelligence (EEG-AI) faces a significant methodological challenge regarding epoch-wise data leakage. This study aims to quantify the implications of this leakage through a comprehensive methodological critique of existing models and proposes a novel, interpretable Dual-Stream Attention-Enhanced Network (DSAEN) architecture optimized for c...

Comparing traditional and AI-enhanced strategies for developing patient decision aids: a multiple case study.

OBJECTIVES: Our objective was to develop and test prompts designed to generate balanced, evidence-based information from artificial intelligence (AI) for the development of patient decision aid (DA) content. We compared the outputs of this AI-enhanced strategy with those produced by an experienced human team using a traditional development approach. METHODS: We conducted a comparative, mixed-metho...

Optical hand kinematics for machine learning-based screening of carpal tunnel syndrome.

Carpal tunnel syndrome (CTS) is usually assessed by clinical examination and electrodiagnostic testing, but these methods may not always be practical ...

Artificial intelligence-based model for identifying anatomical and surgical structures in the videos of laparoscopic left hemicolectomy.

BACKGROUND: Precise surgical procedures are critical to improving the survival outcomes for colon cancer patients. Currently, there is no dedicated in...

Real-world clinical validation of brainstem-based ocular biomarkers for ADHD classification in children and adults.

Current ADHD diagnostic practices rely on subjective rating scales and continuous performance tests with limited specificity. We propose an objective ...

Transcranial photobiomodulation improves prefrontal oxygenation and impulse control in adults with ADHD: a randomized controlled trial.

BACKGROUND: Impulsivity in individuals with attention-deficit/hyperactivity disorder (ADHD) diminishes quality of life. Cortical hypometabolism has be...

Beyond transparency: why Traditional Chinese Medicine (TCM) need explainable artificial intelligence (XAI).

The integration of artificial intelligence (AI) with Traditional Chinese Medicine (TCM) is rapidly expanding, creating new opportunities for digital d...

Integrative multi-omics reveals MHC class II-mediated neuroinflammation and systemic metabolic dysregulation as transdiagnostic drivers in major brain disorders.

Psychiatric, neurodevelopmental, and neurodegenerative disorders, including Alzheimer's disease (AD), attention-deficit/hyperactivity disorder (ADHD),...

Classification of neurodevelopmental disorders and typical development using deep learning and a portable patch-type electroencephalography device.

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) in children and ofte...

Transforming Pulmonary Arterial Hypertension: Key Milestones and Future Perspectives.

Pulmonary arterial hypertension (PAH) is a rare, progressive disease of the precapillary pulmonary arteries, characterized by fibroproliferative vascu...

Prenatal environmental exposures associated with ADHD diagnosis in children: a multicentre exposome analysis.

Attention deficit hyperactivity disorder (ADHD) is one of the most diagnosed neurodevelopmental conditions. While its aetiology is primarily attribute...

Community Health Nurses' Perceptions of Emerging Artificial Intelligence and its Impact on Nursing Practice: An Explanatory Sequential Mixed Methods Study.

BackgroundArtificial intelligence (AI) continues to emerge into nursing practice with much of the AI research being conducted in the acute care sector...

Evaluation of an AI Medical Scribe After 236,153 Notes Generated Across Care Levels in a European Health System: Mixed Methods Retrospective Observational Study.

BACKGROUND: Clinicians spend a substantial share of their working hours on documentation, contributing to workflow inefficiencies, reduced patient-fac...

Habenula as a neural mediator of inattentive traits and sustained attention variability: A 7-Tesla magnetic resonance imaging study.

BACKGROUND: Sustained attention requires continuous engagement and is sensitive to individual differences in motivational processes. Variability in su...

Transdiagnostic behavioral and sociodemographic influences on the cognitive-adaptive functioning gap in neurodivergent children.

Adaptive functioning typically aligns with cognitive ability in the general population, but this relationship appears more complex in neurodivergent p...

Enhancing the Effectiveness of Attention-Deficit/Hyperactivity Disorder Screening Using the SNAP-IV: A Deep Learning Approach.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition requiring early and accurate identification to optimize outco...

Hierarchies of Smell: Structuring the molecular odor space using Semantic Taxonomies and machine learning.

One of the key challenges to predict odor from molecular structure is unarguably our limited understanding of the odor space and the complexity of the...

The role and application of task-state fNIRS in identifying biomarkers in children and adolescents with ADHD: a systematic review.

Attention Deficit Hyperactivity Disorder (ADHD), a prevalent neurodevelopmental condition, urgently requires objective biomarkers to improve diagnosti...

AI-enabled GRADE: How the GRADE Working Group will use automation to rate the certainty of evidence of intervention effects.

OBJECTIVE: The Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group is developing GRADErater (GRADE Rating Automati...

Computational design of low-volatility lubricants for space using interpretable machine learning.

The function and lifetime of moving mechanical assemblies (MMAs) in space depend on the properties of lubricants. MMAs that experience high speeds or ...