Pediatrics

Artificial Intelligence Methods in Early Detection of Autism Spectrum Disorder: A DSM-5 Criterion-Based Systematic Review.

Can Artificial Intelligence (AI) revolutionize early detection of Autism Spectrum Disorder (ASD) by ...

The role of machine learning, deep learning, and MRI findings in the classification of pediatric posterior fossa tumors.

PURPOSE: Pediatric posterior fossa tumors represent a major subset of childhood central nervous syst...

AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults.

IMPORTANCE: The rapid expansion of artificial intelligence (AI) chatbots has coincided with a persis...

Pediatric Clinical Images Without Consent: A Governance Gap in the Long-Term Reuse of Health Data in Digital Health Ecosystems.

Digital health governance frameworks have primarily focused on prospective safeguards, including inf...

Bridging Generations: Leveraging Technology and Artificial Intelligence for Better Research, Outreach, and Daily Practice.

The Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2025 annual meet...

An Active Dry-Contact Continuous EEG Monitoring System for Seizure Detection Applications in Clinical Neurophysiology.

OBJECTIVE: Young children and infants, especially newborns, are highly susceptible to seizures, whic...

Systematic review of foundation models for structured electronic health records.

PURPOSE: Foundation models pretrained on structured electronic health record (EHR) data promise impr...

A Comparative Evaluation of Large Language Models on Pediatric Board-Style Examinations.

OBJECTIVE: To evaluate the performance of 4 leading large language models (LLMs) on pediatric board-...

How Artificial Intelligence Is Changing Neonatal Care.

Integrated analysis of mRNA, circRNA, and miRNA reveals a ceRNA network underlying growth rate differences in the longissimus dorsi muscle of Saba pigs.

The growth rate of pigs is a key factor that determines production efficiency and economic benefits....

Robust and Interpretable AI for Acute Appendicitis: A Simulation-to-Clinical Validation Pipeline.

BACKGROUND AND OBJECTIVE: Accurate and timely diagnosis of Acute Appendicitis remains a major challe...

Unified comparison of machine learning paradigms for blood transfusion prediction in pediatric congenital heart surgery.

Blood transfusion prediction studies in pediatric cardiac surgery have employed direct regression, t...

Prediction of low birth weight using machine learning-based analysis of environmental and maternal risk factors: insights from the Korean CHildren's ENvironmental health Study (Ko-CHENS).

Adverse birth outcomes such as low birth weight (LBW) increase the risk of metabolic disorders and h...

Guideline Adherence in the Diagnosis of PCOS Among Adolescents: Comparing Obstetricians and Gynecologists With Large Language Models.

STUDY OBJECTIVE: Polycystic ovary syndrome in adolescence is a condition associated with long-term c...

Quantitative MRI of pediatric chronic kidney disease and renal fibrosis: potential non-invasive clinical biomarkers.

Chronic kidney disease (CKD) in children is a rare but serious condition characterized by progressiv...

Machine learning-based screening model for Tic disorders comorbid with attention-deficit/hyperactivity disorder in children and SHAP value interpretation: a retrospective observational study.

Tic disorders (TD) are common neurodevelopmental conditions in children and adolescents, characteriz...

Predicting facility delivery and its determinants among reproductive-age women in Ethiopia using machine learning algorithm: evidence from performance monitoring for action Ethiopia 2019 dataset.

BACKGROUND: Facility delivery attended by skilled health professionals is a critical strategy for re...

Pediatric post-acute sequelae of SARS-CoV-2 infection in Taiwan: Insights from the DISCOVER cohort.

The post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID, represent a multifaceted chal...

Predicting growth, water-use efficiency and drought response through machine learning, GWAS and differential expression in Ponderosa pine.

Understanding the molecular basis of phenotypic trait variation is key in improving field performanc...

Real-World Data Needs Real-World Doctors: When Automation Advances Faster Than Clinical Workflow.

Health care is entering an era of unprecedented detection. Artificial intelligence (AI)-driven monit...

Large language model empowered explainable and interpretable mental health analysis.

Concern about expressing depressive symptoms on social media is growing in the digital age. Traditio...