ADHD/ADD

Evaluating virtual reality technology in psychotherapy: impacts on anxiety, depression, and ADHD.

BACKGROUND: Mental health issues pose a significant challenge for medical providers and the general public. The World Health Organization predicts that by 2030, mental health problems will become the leading cause of global disease burden, highlighting the urgent need for effective mental health interventions. Virtual reality-cognitive behavioral therapy (VR-CBT) has emerged as a promising treatme...

Who's that lady? - Applying open source intelligence in a history context.

During a network analysis of the Dutch astronomer and psychologist Rebekka Aleida Biegel (1886-1943), we stumbled upon an often investigated group photo that most likely shows two of her close friends and a third woman posing with Albert Einstein among others in a chemistry laboratory in Zurich while having a tea party. Using data from the Dark Web, face recognition, open source intelligence (OSIN...

Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study.

The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important role in atmospheric secondary particle formation. H...

Signed Curvature Graph Representation Learning of Brain Networks for Brain Age Estimation.

Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing i...

LCGNet: Local Sequential Feature Coupling Global Representation Learning for Functional Connectivity Network Analysis With fMRI.

Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) has greatly advanced ou...

The use of machine learning to understand the role of visual attention in multi-attribute choice.

Whether eye movements (as a measure of visual attention) contribute to the understanding of how multi-attribute decisions are made, is still a matter ...

Artificial intelligence-based drug repurposing with electronic health record clinical corroboration: A case for ketamine as a potential treatment for amphetamine-type stimulant use disorder.

BACKGROUND AND AIMS: Amphetamine-type stimulants are the second-most used illicit drugs globally, yet there are no US Food and Drug Administration (FD...

Predicting neurodevelopmental disorders using machine learning models and electronic health records - status of the field.

Machine learning (ML) is increasingly used to identify patterns that could predict neurodevelopmental disorders (NDDs), such as autism spectrum disord...

Modeling Functional Brain Networks for ADHD via Spatial Preservation-Based Neural Architecture Search.

Modeling functional brain networks (FBNs) for attention deficit hyperactivity disorder (ADHD) has sparked significant interest since the abnormal func...

TPAFNet: Transformer-Driven Pyramid Attention Fusion Network for 3D Medical Image Segmentation.

The field of 3D medical image segmentation is witnessing a growing trend in the utilization of combined networks that integrate convolutional neural n...

Coronary Artery Disease Detection Based on a Novel Multi-Modal Deep-Coding Method Using ECG and PCG Signals.

Coronary artery disease (CAD) is an irreversible and fatal disease. It necessitates timely and precise diagnosis to slow CAD progression. Electrocardi...

Noise-resistant sharpness-aware minimization in deep learning.

Sharpness-aware minimization (SAM) aims to enhance model generalization by minimizing the sharpness of the loss function landscape, leading to a robus...

Exploring potential ADHD biomarkers through advanced machine learning: An examination of audiovisual integration networks.

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition marked by inattention and impulsivity, linked to disruptions in func...

Investigating the impact of an AI-based play activities intervention on the quality of life of school-aged children with ADHD.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that not only impacts children's behavior, lear...

Unlocking the potential: Responsibly embracing artificial intelligence to advance the use of health data and analytics at the Canadian Institute for Health Information.

Canadian Institute for Health Information (CIHI) is looking to modernize and adopt new ways of working. This incudes the use of new technology, includ...

Evaluation of physical risk factors by fuzzy failure mode and effects analysis: an apparel mill example.

This study investigates the evaluation of risks faced by employees in a selected large-scale apparel mill using a risk assessment method with a fuzzy ...

Advancements in maize disease detection: A comprehensive review of convolutional neural networks.

This review article provides a comprehensive examination of the state-of-the-art in maize disease detection leveraging Convolutional Neural Networks (...

Using neural networks for image analysis in general physiology.

An article with three goals, namely, to (1) provide the set of ideas and information needed to understand, at a basic level, the application of convol...

Sensory Stimulation and Robot-Assisted Arm Training After Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Functional recovery after stroke is often limited, despite various treatment methods such as robot-assisted therapy. Repetitiv...

Insights Into Detecting Adult ADHD Symptoms Through Advanced Dual-Stream Machine Learning.

Advancements in machine learning offer promising avenues for the identification of ADHD symptoms in adults, an endeavour traditionally encumbered by t...