ADHD/ADD

DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to quantify predictive uncertainty at each voxel during a single inference. To do so, we design an evidence-based ensemble learning framework for uncertai...

A discriminative multi-modal adaptation neural network model for video action recognition.

Research on video-based understanding and learning has attracted widespread interest and has been adopted in various real applications, such as e-healthcare, action recognition, affective computing, to name a few. Amongst them, video-based action recognition is one of the most representative examples. With the advancement of multi-sensory technology, action recognition using multi-modal data has r...

A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study.

Borderline personality disorder (BPD) is associated with a high risk of suicide. Despite several risk factors being known, identifying vulnerable pati...

Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.

Antiepileptics and antidepressants are frequently prescribed for chronic pain, but their efficacy and potential adverse effects raise concerns, inclu...

Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples.

Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of established biomarkers, accurate diagnosis and ef...

Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.

Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significa...

Emotion recognition using multi-scale EEG features through graph convolutional attention network.

Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in pa...

Combining Group Contribution Method and Semisupervised Learning to Build Machine Learning Models for Predicting Hydroxyl Radical Rate Constants of Water Contaminants.

Machine learning is an effective tool for predicting reaction rate constants for many organic compounds with the hydroxyl radical (HO). Previously rep...

Objective approach to diagnosing attention deficit hyperactivity disorder by using pixel subtraction and machine learning classification of outpatient consultation videos.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common childhood neurodevelopmental disorder, affecting between 5% and 7% of school-a...

Cost-Utility Analysis of Add-on Cannabidiol vs Usual Care Alone for the Treatment of Seizures in Patients With Treatment-Resistant Lennox-Gastaut Syndrome or Dravet Syndrome in the Netherlands.

Lennox-Gastaut syndrome (LGS) and Dravet syndrome (DS) are severe, treatment-refractory, epileptic encephalopathies that often develop in infancy or ...

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 tha...

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 pho...

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...