Pediatrics

Epidemiological Trajectories and Quality of Care Disparities of MASLD in Asia, 1990-2023.

BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated ste...

Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression.

Maternal postpartum depression (PPD) is a significant mental health issue that affects over 15% of m...

Corrigendum to "Deep learning in fetal, infant, and toddler neuroimaging research"[Dev. Cognit. Neurosci. (2026), 101680].

Peripheral Retinal Vessel Density in Children and Adolescents with Myopia: A Deep Learning Assessment.

INTRODUCTION: This study investigated the effect of axial length (AL) on peripheral retinal vessel d...

Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database.

BACKGROUND: Surgical site infections (SSIs) cause substantial postoperative morbidity in children. D...

Neuroprognostication via Radiomics and Machine Learning Following Neonatal Hypoxic-Ischemic Insult.

OBJECTIVE: To produce objective predictions of neurodevelopmental outcomes after perinatal hypoxic-i...

Expanding the horizon of oculomics: A narrative review on the emerging roles of the anterior segment and mobile health.

Oculomics uses the eye to gain insights into systemic health. Although initially focused on retinal ...

Minor salivary gland biopsy in Sjogren's disease: a diagnostic and prognostic tool toward precision medicine.

Minor salivary gland biopsy occupies a distinctive position in the evaluation of Sjögren disease (Sj...

Deep learning-based cerebellar segmentation on T2-weighted fluid-attenuated inversion recovery magnetic resonance imaging for detecting cerebellar hypoplasia/atrophy in infants.

BACKGROUND: Accurate measurement of cerebellar volume is crucial for diagnosing cerebellar atrophy o...

A modern radiologist's guide to artificial intelligence.

Artificial intelligence (AI) has the potential to disrupt many fields, and radiology is no exception...

ContraIndicator: A Natural Language Processing-Based Approach to Potential Drug-Drug Interaction Detection in Pediatric Intensive Care.

BACKGROUND AND OBJECTIVES: The intricate nature of pediatric patients' physiology and the frequent a...

Whole-body magnetic resonance imaging in rheumatology: advancements, key applications and future perspectives.

Whole-body magnetic resonance imaging (WB-MRI) is widely used in rheumatology to assess peripheral a...

Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.

BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical proc...

Predicting vesicoureteral reflux outcomes using artificial intelligence: A critical appraisal using APPRAISE-AI.

Vesicoureteral reflux (VUR) is a common congenital urinary tract anomaly in children, associated wit...

Development of retrieval-augmented generation-based large language model for drug-induced liver injury using Livertox data.

BACKGROUND: Idiosyncratic DILI is a complex clinical challenge requiring timely and accurate decisio...

Crucial Conversations: Psychiatric Diagnosis and Shared Decision-Making With Adolescents in the Age of Social Media and Artificial Intelligence.

Retinal Biomarkers for Cardiovascular Disease Prediction: A Review Focused on CHD AHD Valvular Disorders and Cardiomyopathies.

INTRODUCTION: Cardiovascular diseases (CVDs) remain the leading cause of global mortality, with cong...

Machine Learning Tools for Predicting Pediatric Urinary Tract Infections Caused by ESBL-producing Bacteria.

BACKGROUND: The prevalence of pediatric urinary tract infections (UTIs) caused by extended-spectrum ...

Mediated Electrochemical Probing and Machine Learning for Cysteine and Reduced Monoclonal Antibody Quantification.

Biopharmaceutical manufacturing requires robust analytics and process controls throughout production...

Global research trends in robotic-assisted thoracoscopic surgery: a multidimensional analysis from 2000 to 2025.

OBJECTIVE: Robotic-assisted thoracoscopic surgery (RATS) has transformed thoracic surgery, yet fragm...

Clinical Applications of Data Science and Machine Learning in the Pediatric Cardiac Intensive Care Unit.

To synthesize and critically appraise applications of machine learning (ML) in pediatric cardiac int...