BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is characterized by impairments in executive functioning, particularly response inhibition (RI). This study combines time-domain analysis and source analyses of event-related potentials (ERP...
Social anxiety disorder (SAD) is a prevalent psychiatric condition with significant psychological and socioeconomic consequences. While its psychological characteristics are well-documented, the underlying molecular mechanisms remain poorly understoo...
Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous system and is predominantly diagnosed in adults, making pediatric cases rare and underrepresented in medical research. This paper introduces the first ...
While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we use artificial intelligence ...
BACKGROUND: Accurately predicting children's memory and suggestibility in forensic contexts, such as child sexual abuse (CSA) investigations, remains challenging for human professionals. Large Language Model (LLM), as an advanced natural language pro...
BACKGROUND: Early diagnosis is crucial for reducing disability and improving long-term prognosis in patients with systemic Juvenile Idiopathic Arthritis (sJIA), but it remains a significant challenge. This study aims to identify non-invasive biomarke...
BACKGROUND: Height gain in children with growth disorders undergoing recombinant human growth hormone (rhGH) therapy shows considerable variability. Predicting treatment outcomes is essential for optimizing individualized treatment strategies.
In the rapidly evolving field of dental intelligent healthcare, where Artificial Intelligence (AI) plays a pivotal role, the demand for multimodal datasets is critical. Existing public datasets are primarily composed of single-modal data, predominant...
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