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Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease.

Hepatology communications
BACKGROUND: Children with autoimmune liver disease (AILD) may develop fibrosis-related complications necessitating a liver transplant. We hypothesize that tissue-based analysis of liver fibrosis by second harmonic generation (SHG) microscopy with art...

Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Real-time monitoring of pediatric epileptic seizures poses a significant challenge in clinical practice. In recent years, machine learning (ML) has attracted substantial attention from researchers for diagnosing and treating neurological ...

A neural network to create super-resolution MR from multiple 2D brain scans of pediatric patients.

Medical physics
BACKGROUND: High-resolution (HR) 3D MR images provide detailed soft-tissue information that is useful in assessing long-term side-effects after treatment in childhood cancer survivors, such as morphological changes in brain structures. However, these...

Does machine learning improve prediction accuracy of the Endoscopic Third Ventriculostomy Success Score? A contemporary Hydrocephalus Clinical Research Network cohort study.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
PURPOSE: This Hydrocephalus Clinical Research Network (HCRN) study had two aims: (1) to compare the predictive performance of the original ETV Success Score (ETVSS) using logistic regression modeling with other newer machine learning models and (2) t...

A neural network integrated mathematical model to analyze the impact of nutritional status on cognitive development of child.

Computers in biology and medicine
Cognitive development is a crucial developmental aspect of children. It is a concise field of study in psychology and neuroscience that focuses on various developmental aspects of the brain. Among all other factors, nutritional status is believed to ...

Limbic/paralimbic connection weakening in preschool autism-spectrum disorder based on diffusion basis spectrum imaging.

The European journal of neuroscience
This study aims to investigate the value of basal ganglia and limbic/paralimbic networks alteration in identifying preschool children with ASD and normal controls using diffusion basis spectrum imaging (DBSI). DBSI data from 31 patients with ASD and ...

ChatGPT-4o's performance on pediatric Vesicoureteral reflux.

Journal of pediatric urology
INTRODUCTION: Vesicoureteral reflux (VUR) is a common congenital or acquired urinary disorder in children. Chat Generative Pre-trained Transformer (ChatGPT) is an artificial intelligence-driven platform offering medical information. This research aim...

Understanding the role of hormones in pediatric growth: Insights from a double-debiased machine learning approach.

Steroids
This study investigates the causal relationships between hormone levels and growth and development of children, focusing specifically on height disparities in cases of dwarfism. Besides utilizing double-debiased machine learning approach, the study i...

Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol.

BMJ open
INTRODUCTION: Paediatric fractures are common but can be easily missed on radiography leading to potentially serious implications including long-term pain, disability and missed opportunities for safeguarding in cases of inflicted injury. Artificial ...