Pediatrics

Driving Mechanisms and Future Trends of Migraine and Tension-Type Headache Burden in G20 Countries: A Comparative Analysis Utilizing Decomposition Analysis and Explainable Machine Learning.

INTRODUCTION: Migraine and tension-type headache (TTH) are leading causes of neurological disability globally. While their macro-trends are documented, the nonlinear drivers and the regulatory role of socio-economic development across G20 countries remain under-explored. METHODS: Based on Global Burden of Disease (GBD) 2023 data, the headache burden across G20 members was quantified. Developmental...

Open dataset and deep learning model for intelligent diagnosis of neonatal respiratory distress syndrome and aspiration syndrome in newborns.

Neonatal pulmonary diseases such as aspiration syndrome (AS) and respiratory distress syndrome (NRDS) require timely diagnosis, yet manual interpretation of neonatal X-rays is labor-intensive and subjective. To support AI-assisted diagnosis, we constructed the first Chinese neonatal pulmonary ailment dataset (NPA), covering both normal and diseased cases of varying severity. However, the NPA datas...

Using natural language processing to support digital communication in adolescents and young adults with autism spectrum disorder.

BACKGROUND: Autism Spectrum Disorder (ASD) is characterized by social communication challenges, including difficulties interpreting figurative languag...

Artificial intelligence meets pediatric orthopedics: A comparative analysis of ChatGPT-4o, Gemini 2.0, and Claude 3.5 in detecting supracondylar humeral fractures.

BACKGROUND: Supracondylar humeral fractures constitute 10-16% of pediatric skeletal injuries, requiring timely diagnosis to prevent neurovascular comp...

[Diagnosis of congenital heart disease using Deep Learning in pediatric chest X-rays: A proof of concept].

BACKGROUND: In Mexico, congenital heart diseases (CHD) are the most common birth defects. Despite their high mortality rate, many CHD are not detected...

An AI-Assisted Tool to Predict Continuous Glucose Monitor Adherence in Children With Type 1 Diabetes in Oman: Protocol for a Multiphase Mixed Methods Translational Study.

BACKGROUND: Type 1 diabetes mellitus (T1DM) in children requires sustained self-management to achieve glycemic targets. Continuous glucose monitoring ...

An interpretable machine learning model for outpatient referral risk assessment in pediatric biliary atresia after Kasai portoenterostomy.

OBJECTIVES: To develop an interpretable model using routine outpatient data to assist risk stratification and referral assessment in children with bil...

Predicting Neonatal Respiratory Outcomes Using Machine Learning: A Systematic Review Through a Life Course Lens.

BACKGROUND: Neonatal respiratory outcomes remain leading drivers of neonatal intensive care unit (NICU) morbidity, mortality, and prolonged hospitaliz...

Geospatial approaches for mapping zero-dose prevalence and routine childhood immunisation coverage in low- and lower-middle-income countries: A scoping review.

BACKGROUND: Zero-dose (ZD) children remain a critical public health concern, particularly in low- and lower-middle-income countries (LLMICs), where ov...

Analysis of health anxiety trajectories in rabies exposure patients based on machine learning.

OBJECTIVE: To identify the dynamic evolution trajectory of health anxiety in patients with initial rabies exposure and to conduct predictive analysis ...

RootHairAreaFinder: an image processing method for quantifying barley root growth and root hairs simultaneously in a flat rhizotron system.

Root system architecture and root hairs highly influence plant resource uptake, yet their simultaneous quantification at the whole-plant scale remains...

Characteristic differences in somatosensory ERP components in Go/No-go paradigm between adolescents and adults.

This study investigated developmental differences in motor execution and inhibition by comparing somatosensory event-related potentials (ERPs) between...

Dual-input deep learning bone age assessment in late adolescence using hand and knee radiographs.

OBJECTIVE: To develop and internally evaluate an age-assisted dual-input model for bone age assessment in late adolescence using paired hand-wrist and...

Frequency-decomposed EEG microstate analysis reveals altered cross-frequency coordination in adolescent major depressive disorder.

Adolescent major depressive disorder (MDD) involves alterations in large‑scale brain network dynamics. However, conventional EEG microstate studies ty...

Skyer: a novel benchmark for evaluating the effectiveness of large language models in emergency department triage.

OBJECTIVES: Emergency department (ED) overcrowding causes diagnostic challenges, prolonged wait times, and impairs appropriate triage, often due to hu...

What drives generational differences in subjective well-being? A machine learning study of Chinese migrant workers in the Yangtze River Delta.

The subjective well-being of migrant workers amid China's rapid urbanization has emerged as a critical issue, intersecting social policy and mental he...

A classification model for predicting corticosteroid and cyclosporin: A responsiveness in pediatric idiopathic uveitis.

BACKGROUND: To identify serum metabolic biomarkers that distinguish corticosteroid and cyclosporin A (CS & CsA) resistant pediatric idiopathic uveitis...

Development and validation of a multimodal deep learning model for the radiographic classification of pediatric femoral neck fractures.

BACKGROUND: An alternative classification system for categorizing pediatric femoral neck fractures (PFNFs) has been shown to have significant clinical...

Single lead electrocardiographic detection of left ventricular systolic dysfunction in pediatric and congenital heart disease.

Portable, scalable, and accessible artificial intelligence (AI)-enabled smartwatch technology shows promise as a cardiovascular risk stratification st...

Assessing the accuracy of ChatGPT responses to caregiver questions in pediatric neurology: an observational study.

ChatGPT has seen increased use by caregivers as a source of medical information. Pediatric neurology has added complexities because there are various ...