UNLABELLED: Growth assessment in achondroplasia requires disorder-specific growth charts incorporating sex- and age-specific values. Manual calculations are tedious and subject to error. We present an artificial intelligence (AI)-assisted tool that a...
BACKGROUND: Oral microbiota is a major etiological factor in the development of dental caries. Next-generation sequencing techniques have been widely used, generating vast amounts of data which is underexplored. The advancement of artificial intellig...
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Jul 15, 2025
BACKGROUND: Survival of patients with high-risk hepatoblastoma remains low, and early identification of high-risk hepatoblastoma is critical.
Ecotoxicology and environmental safety
Jul 12, 2025
Lead exposure poses substantial long-term health risks, accounting for over 900,000 annual deaths worldwide and impairing cognitive development in more than 800 million children. Recent studies have indicated elevated soil lead contamination levels o...
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: 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.
Intravenous immunoglobulin (IVIG) has been established as the first-line therapy for Kawasaki disease (KD). However, approximately 10%-20% of pediatric patients exhibit IVIG resistance. Current machine learning (ML) models demonstrate suboptimal pred...
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