Pediatrics

ADHD/ADD

Latest AI and machine learning research in adhd/add for healthcare professionals.

6,134 articles
Stay Ahead - Weekly ADHD/ADD research updates
Subscribe
Browse Specialties
Showing 64-84 of 6,134 articles
Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

The Guided Imagery technique is reported to be used by therapists all over the world in order to inc...

ZnO nanoflower-mediated paper-based electrochemical biosensor for perfect classification of cardiac biomarkers with physics-informed machine learning.

The widespread exposure of acute myocardial infarction globally demands an ultrasensitive, rapid, an...

Automated ADHD detection using dual-modal sensory data and machine learning.

This study explores using dual-modal sensory data and machine learning to objectively identify Atten...

Narrative Search Engine for Case Series Assessment Supported by Artificial Intelligence Query Suggestions.

INTRODUCTION: Manual identification of case narratives with specific relevant information can be cha...

Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia.

Regulating inflammatory microglia presents a promising strategy for treating neurodegenerative and a...

Is it necessary? A framework for assessing the utility of A.I. in HRM practices.

Artificial Intelligence is expected to be a value-adding intervention in HRM processes; however, the...

Author name disambiguation based on heterogeneous graph neural network.

With the dramatic increase in the number of published papers and the continuous progress of deep lea...

Optimizing depression detection in clinical doctor-patient interviews using a multi-instance learning framework.

In recent years, the number of people suffering from depression has gradually increased, and early d...

Better off alone? Artificial intelligence can demonstrate superior performance without clinician input.

Recent studies challenge the assumption that human-artificial intelligence (AI) collaboration is uni...

A systematic literature review of machine learning techniques for the detection of attention-deficit/hyperactivity disorder using MRI and/or EEG data.

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition common in teenager...

Interpretable machine learning approaches for children's ADHD detection using clinical assessment data: an online web application deployment.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a prevalent mental disorder character...

Carbon source dosage intelligent determination using a multi-feature sensitive back propagation neural network model.

The carbon reduction concept drives the development of low-carbon and sustainable wastewater treatme...

Augmented Intelligence-Based Interference Pattern Analysis (AI-IPA) in Concentric Needle Electromyography.

INTRODUCTION/AIMS: To add objectivity to the routine needle electromyography examination, we describ...

A novel framework to predict ADHD symptoms using irritability in adolescents and young adults with and without ADHD.

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder ...

Differentiating Functional Connectivity Patterns in ADHD and Autism Among the Young People: A Machine Learning Solution.

OBJECTIVE: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions wit...

Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder.

Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD...

Knowledge Distillation Guided Interpretable Brain Subgraph Neural Networks for Brain Disorder Exploration.

The human brain is a highly complex neurological system that has been the subject of continuous expl...

Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation.

This work focuses on the efficiency of the knowledge distillation approach in generating a lightweig...

Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.

Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, an...

Detecting noncredible symptomology in ADHD evaluations using machine learning.

INTRODUCTION: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becomin...

Browse Specialties