Latest AI and machine learning research in adhd/add for healthcare professionals.
Contrastive learning has gained dominance in sequential recommendation due to its ability to derive ...
Sequential Recommendation is based on modelling sequential dependencies in user interactions to prod...
Graph Neural Networks (GNNs) have received extensive research attention due to their powerful inform...
To use electronic health record (EHR) data to develop a scalable and transferrable model to predict...
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusi...
Research on video-based understanding and learning has attracted widespread interest and has been ad...
Borderline personality disorder (BPD) is associated with a high risk of suicide. Despite several ris...
Antiepileptics and antidepressants are frequently prescribed for chronic pain, but their efficacy a...
Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of...
Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-smal...
Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various ...
Machine learning is an effective tool for predicting reaction rate constants for many organic compou...
BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common childhood neurodevelopmental...
Lennox-Gastaut syndrome (LGS) and Dravet syndrome (DS) are severe, treatment-refractory, epileptic ...
BACKGROUND: Mental health issues pose a significant challenge for medical providers and the general ...
Triple-negative breast cancer (TNBC) lacks estrogen, progesterone, and HER2 expression, accounting f...
During a network analysis of the Dutch astronomer and psychologist Rebekka Aleida Biegel (1886-1943)...
The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important r...
Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for e...
Analysis of functional connectivity networks (FCNs) derived from resting-state functional magnetic r...
Whether eye movements (as a measure of visual attention) contribute to the understanding of how mult...