Pediatrics

Meconium metabolomic profiling dysregulation and neonatal brain injury in selective fetal growth restriction.

BACKGROUND: Meconium serves as a valuable biological matrix for characterizing fetal metabolic signatures throughout gestation. Selective fetal growth restriction (sFGR) is associated with adverse neurological outcomes, potentially mediated by underlying metabolic perturbations. However, the specific relationship between dysregulated meconium metabolome and brain injury in sFGR remains poorly unde...

A comparative evaluation of two large language models in pediatric dentistry.

A methodological comparative analysis of monetary policy and trade openness on economic growth in West Africa: Does language play a role?

The study examines the effect of monetary policy and trade openness on economic growth in the ECOWAS countries. Using panel regression analysis and th...

Impacts of delayed influenza vaccination on clinical outcomes in ICU-admitted patients with influenza: A retrospective cohort study.

BACKGROUND: Influenza vaccination is an effective measure for reducing the risk of severe influenza infection. However, the task of achieving adequate...

Prevalence of intestinal parasites in a tertiary care hospital and utility of AI-assisted fecal analyzer for their detection.

INTRODUCTION: Intestinal parasitic infections, caused by protozoa and helminths, can lead to malnutrition, anaemia, and impaired growth. While direct ...

Understanding public perceptions of cultural ecosystem services in urban coastal wetland ecological restoration areas: A social media-based large language model approach.

Understanding public perceptions of cultural ecosystem services (CES) in urban coastal wetland ecological restoration areas was essential for coastal ...

Integrated single-cell analyses of affinity-tested B cells enable the identification of a gene signature to predict antibody affinity.

Advancements in single-cell technologies and deep sequencing have expanded the B cell repertoire available for antibody discovery. However, selecting ...

Patients' Attitudes and Beliefs Toward Artificial Intelligence Use in Cancer Care: Cross-Sectional Survey Study.

BACKGROUND: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little is known about how patients perceive these applic...

HappyMums mobile application study protocol: use of a smartphone application to gather data predictive of antenatal depression.

INTRODUCTION: Mobile health (mHealth) technologies have become increasingly popular for monitoring mental health symptoms and lifestyle behaviours, an...

Deep neural network-based analysis of voice biomarkers for monitoring treatment response in adolescent major depressive disorder.

BACKGROUND: In adolescents, identifying objective biomarkers for treatment response is crucial for the development of effective interventions. Voice-b...

Utilizing optical coherence tomography and machine learning to identify vision abnormalities in pediatric neurofibromatosis type 1 patients.

Neurofibromatosis type 1 (NF-1) is a genetic disorder associated with a high risk of vision loss in children. Optical coherence tomography (OCT) provi...

Validation of an AI model for pediatric myelin maturation age assessment and benefits for junior radiologists.

Clinical Profile of Neurosurgical Consultations from the Emergency Department : A Retrospective Analysis.

OBJECTIVE: This study aimed to retrospectively analyze consultations requested from the emergency departments (EDs) to the neurosurgery (NS) departmen...

Multiple weak biases support adaptive choices without prior experience: a self-supervised strategy.

From social interaction to foraging, the survival of newborn animals depends on their ability to make adaptive decisions without prior experience. Whi...

3D-QALAS synthetic MRI with Zero-DeepSub in children: initial experience including post-contrast imaging feasibility.

BACKGROUND: Magnetic resonance imaging (MRI) in children requires multiple sequences, leading to lengthy exams and motion-related challenges. Syntheti...

Prediction of Fontan failure and correlates of Fontan-associated liver disease severity using machine learning and radiomic features from multi-parametric abdominal MRI.

BACKGROUND: Fontan-associated liver disease (FALD) is associated with morbidity and mortality in patients with palliated single ventricle congenital h...

Predicting Infant Sleep Patterns From Postpartum Maternal Mental Health Measures: Machine Learning Approach.

BACKGROUND: Postpartum maternal mental health (MMH) symptoms, including depression, anxiety, and childbirth-related post-traumatic stress disorder, ar...

AI based sagittal spinal posture assessment for adolescent screening in low resource school settings.

Adolescent spinal postural deviations are rising across Southeast Asia, driven by prolonged screen exposure and limited access to clinical screening i...

Detection of Swallowing Abnormalities in Pediatric FEES Recordings Using Rule-Based and Model-Based Methods.

Pediatric swallowing dysfunction (SwD) poses serious health risks, including aspiration, malnutrition, and recurrent respiratory infections, making ea...

Machine learning-based prediction of acute and complicated appendicitis using readily available data in low-resource settings.

BACKGROUND: Acute appendicitis often presents diagnostic challenges, especially in pediatric and elderly patients. Delays can cause serious complicati...