BACKGROUND: The multifactorial mechanisms driving childhood obesity, a global public health challenge, are yet to be fully elucidated. We aimed to develop and externally validate three widely applied machine learning models alongside logistic regress...
Diabetes is a chronic condition that affects a substantial portion of the global population and is linked to elevated mortality rates and a range of severe health complications. Despite its clinical importance, progress in diabetes research is often ...
PURPOSE: Decision-making for orchiectomy following testicular torsion often relies on subjective clinical evaluations. This study investigates the efficacy of machine learning (ML) models in objectively predicting post-torsion testicular viability, a...
UNLABELLED: Early identification of children at high risk for moderate-to-severe obstructive sleep apnea (OSA) is crucial for timely intervention, yet is often hindered by limited access to polysomnography (PSG). We aimed to develop an interpretable ...
INTRODUCTION: The substantial case detection gap in the field of child tuberculosis (TB) disease is largely driven by inadequate diagnostic tools and approaches. Chest radiographs (CXRs) remain a key component in the evaluation of children and young ...
BACKGROUND: Pediatric patients under general anesthesia are particularly vulnerable to hypoxemia, which can lead to rapid oxygen desaturation. This vulnerability necessitates heightened vigilance from anesthesiologists, making pediatric anesthesia ma...
PURPOSE: Differentiating among exanthematous diseases is frequently challenging due to their overlapping symptomatology. We, therefore, aimed to evaluate the diagnostic accuracy of a consultant physician, a resident physician, and various AI models (...
INTRODUCTION: T1w/T2w ratio mapping, combining voxel-wise signal intensities in T1-weighted (T1w) and T2-weighted (T2w) structural MRI, has been used to investigate cortical architecture in the brain, but has also shown promise in tissue discriminati...
The impact of Pivotal Response Treatment (PRT) assisted by the social robot Pepper on the emotional regulation and treatment adherence of children with autism spectrum disorder (ASD) and their caregivers is explored. Given the integration of technolo...
BACKGROUND/OBJECTIVES: This study aimed to evaluate the performance of deep learning models for recognizing facial expressions of children with autism through face recognition technologies.
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