ADHD/ADD

Comorbidity-aware transfer learning for neuro-developmental disorder diagnosis.

Neurodevelopmental disorders (NDDs) are characterized by impairments in cognition, communication, behavior, and adaptive functioning, placing increasing strain on healthcare resources for neuroimaging-based diagnosis. While deep learning-based computer-aided diagnosis (CAD) systems offer potential solutions, the complex spatiotemporal dynamics inherent in functional magnetic resonance imaging (fMR...

Evaluating Public Sentiment on Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Compared With Other Mental Health Disorders From Posts on X (Formerly Known as Twitter): Longitudinal Analysis.

BACKGROUND: Neurodevelopmental disorders, especially attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), have seen a marked rise in public attention, yet research on public opinion remains limited. Social media analysis offers real-time, unfiltered insights into public perceptions, enabling empirical examination of public attitudes and opinions. OBJECTIVE: This stud...

Ischaemia in tuberculous meningitis: update on pathophysiology, clinical predictors and management.

PURPOSE OF REVIEW: Tuberculous meningitis (TBM) is a severe manifestation of Mycobacterium tuberculosis infection, associated with high mortality and ...

Understanding bias in older drivers' self-reported driving styles using naturalistic driving data.

OBJECTIVE: Accurate self-assessment of driving performance is critical for maintaining safety and mobility among older adults. However, many older dri...

AI Models for Surgical Decision Support in Spontaneous Intracerebral Hemorrhage: A Systematic Review in Relation to Trials and Guidelines.

Artificial intelligence (AI) applications for spontaneous intracerebral hemorrhage (ICH) are rapidly expanding, particularly in perioperative imaging ...

Challenges in translating AI-driven ASD/ADHD diagnosis: A methodological systematic review.

BACKGROUND: Early and accurate diagnosis of neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention-deficit/hypera...

Classification of depressed and non-depressed MCI and non-depressed cognitively normal individuals using resting-state metrics: A multi-group study with machine learning and graph reinforcement learning.

Depressive symptoms frequently co-occur in individuals with Mild Cognitive Impairment (MCI) and are thought to accelerate neurodegenerative progressio...

Development and Validation of Machine Learning Models for Predicting Early Cognitive Decline Using Home Sensor-Derived Behavioral Data: Sensors in-Home for Elder Wellbeing (SINEW) Cohort Study.

BACKGROUND: As the global population continues to age, the prevalence of geriatric conditions, including dementia and frailty, is also increasing. Ear...

Artificial Intelligence as an Add-On Instrument in Fetal Ultrasound; Sonographers' and Obstetricians' Expectations.

OBJECTIVE: Artificial intelligence applications (AIA) in fetal ultrasound are rapidly evolving, yet their integration into routine clinical practice r...

Attention unleashed: Creative therapy for thoughtful transformation.

Various factors-motivation, interest, fatigue, and external stimuli-influence creative mental processes and attention control (AC). Creative thinking ...

Measuring Accuracy (Classification Probabilities, Positive, and Negative Predictive Values) of Executive Function Electroencephalogram Metrics in Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for and Perspectives From the SINCRONIA Study.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) is the most prevalent neurodevelopmental disorder worldwide, affecting approximately 5%-7%...

Comparison of cognitive ability and its distribution between men with autism spectrum disorder and attention-deficit/hyperactivity disorder.

OBJECTIVES: Clarification of the strengths and weaknesses of cognitive ability is essential to our understanding of the characteristics of autism spec...

3D ADHD-Net and DeepTrace: Decoding ADHD from EEG with neurophysiological insights.

EEG-based ADHD diagnosis models suffer from two persistent issues: data leakage and the lack of physiologically grounded interpretability, limiting cl...

Optimized Complex-Valued Spatio-Temporal Graph Convolutional Networks for attention deficit hyperactivity disorder detection in pediatric EEG signals.

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition affecting mood, anxiety, learning, and sleep. Electroencephalogram (...

Neuroanatomy reflects individual variability in impulsivity in youth.

Individual differences in neural circuits underlying emotional regulation, motivation, and decision-making are implicated in many psychiatric illnesse...

Digital diagnostics, biomarkers and therapeutics in an evolving healthcare system: From promise to practice.

Health care is shifting towards a digital-guided system, integrating digital diagnostics, biomarkers and therapeutics in many care pathways. However, ...

High diagnostic accuracy of a resnet50-based deep learning model for osteochondral lesions of the talus on magnetic resonance imaging.

OBJECTIVES: This study aims to evaluate the diagnostic performance of a ResNet50-based convolutional neural network (CNN) in detecting osteochondral l...

Targeting autophagy in Duchenne muscular dystrophy: mechanistic insights and emerging therapeutic strategies.

Duchenne muscular dystrophy (DMD) is a severe X-linked myopathy characterised by progressive skeletal and cardiac muscle degeneration, loss of ambulat...

Better together: what can state-of-the-art ML models add to thyroid nodule diagnostics?

Perspectives on How Sociology Can Advance Theorizing About Human-Chatbot Interaction and Developing Chatbots for Social Good.

Recently, research into chatbots (also known as conversational agents, artificial intelligence agents, or voice assistants), which are computer applic...