Pediatrics

Antibiotic Duration and Critical Illness After Culture-Negative Late-Onset Sepsis Evaluation in Infants Born Preterm.

OBJECTIVE: To characterize antibiotic administration patterns among very low birth weight (VLBW, < 1...

A RISKmilk framework for predicting drug and chemical exposure in human milk during breastfeeding.

BACKGROUND: Medication decisions during breastfeeding are often made with limited quantitative evide...

Male infertility research for the ART clinic: priorities to enhance patient outcomes, education and wellbeing.

BACKGROUND: Men attending ART clinics often have poor fertility awareness and are typically overlook...

Development and validation of a model for stratifying haematological malignancy risk in primary care using basic blood tests.

Haematological malignancies are rare in primary care and are hard to predict. Existing prediction mo...

Evaluating the accuracy and comprehensiveness of GPT-4 as a patient information tool for pectus deformities.

BackgroundPectus excavatum and carinatum are the most common anterior chest wall deformities in chil...

Predicting relapse in pediatric IgA vasculitis in the era of machine learning: an explainable hybrid ensemble model.

OBJECTIVES: This study aimed to develop an explainable hybrid ensemble machine learning (ML) model t...

Bullying Victimization, Depressive Symptoms, and Suicide Among U.S. High School Adolescents: Protective Effects of School Connectedness and Parental Monitoring.

Suicidal thoughts and behaviors (STBs) among U.S. adolescents remain a public health concern and are...

Trite But True: Children Are Not Little Adults-Advancing Artificial Intelligence in Pediatric Radiology.

A novel real-time computer vision and artificial intelligence based hand function rehabilitation program for children with cerebral palsy.

PURPOSE: To evaluate the effectiveness of a real-time computer vision and artificial intelligence(AI...

CT image-based evaluation of phantom-derived DLP-to-effective dose conversion factors for adult abdomen-pelvis CT.

Effective dose is used in computed tomography (CT) as a population-level quantity for radiation prot...

Predictors of Geographic Atrophy Growth and Visual Decline in a longitudinal Asian cohort.

PURPOSE: To characterize GA growth and visual outcomes in Asian eyes with geographic atrophy (GA) se...

Diagnostic Accuracy of Deep Learning for Detection of Incipient and Advanced Radiographic Interproximal Caries in Mixed Dentition Periapical Radiographs.

OBJECTIVES: This study aimed to develop and compare deep-learning models for detecting proximal cari...

Early identification of Prader-Willi syndrome in newborns using facial phenotype-based machine learning.

BACKGROUND: Existing facial models for Prader-Willi syndrome (PWS) demonstrate limited accuracy in n...

[Oncology Society of Chinese Medical Association guideline for clinical diagnosis and treatment of lung cancer (2026 edition)].

To further standardize the prevention and management of lung cancer in China, improve the level of d...

Distinct clinical patterns of preterm infants vulnerable to intestinal injury identified by unsupervised clustering.

BACKGROUND: Current necrotizing enterocolitis (NEC) diagnostic criteria fail to capture the full spe...

Imaging subtypes reveal distinct biological substrates and disability profiles in multiple sclerosis.

Multiple sclerosis is characterized by marked biological heterogeneity that is only partly captured ...

A co-learning framework for maternal and pediatric pharmacotherapy knowledge gap discovery.

OBJECTIVE: Pregnant and breastfeeding women, along with children, represent populations persistently...

From beta thresholds to learned control: machine learning in adaptive deep brain stimulation.

Deep brain stimulation (DBS) has transformed the treatment of Parkinson's disease by modulating path...

Clinical characteristics, pathological comorbidities, BMI-for-age Z-score, and machine learning-based exploration of postoperative enterocolitis in iIntestinal neuronal dysplasia: a 20-year retrospective study.

PURPOSE: Intestinal neuronal dysplasia (IND) is a congenital enteric neuropathy characterized by abn...

Stakeholder Perspectives on the Integration of AI in Diabetes Care: Systematic Review of Qualitative Studies.

BACKGROUND: AI is increasingly being integrated into diabetes care, with growing evidence supporting...

A Hierarchical Machine Learning-Based Framework for Clinical Decision Support in Foot Orthosis Prescription: Algorithm Development and Validation Study.

BACKGROUND: Foot orthosis prescription is a complex clinical decision-making process that involves s...