Pediatrics

Unveiling Roots of Chinese Adolescent Cyberbullying Through Explainable Machine Learning Approach.

Cyberbullying poses a substantial threat to adolescents' well-being, yet prevention efforts remain limited by insufficient understanding of its multilevel determinants. Guided by ecological systems theory, this study applies explainable machine learning (ML) to examine factors associated with cyberbullying perpetration across individual, family, peer, class, school, and online contexts. Questionna...

The Mediating Role of Eudaimonic Well-Being in the Effect of Perceived Poverty on Quality of Life in the Elderly.

BACKGROUND: This study was conducted to examine the mediating role of eudaimonic well-being in the effect of perceived poverty on quality of life in the elderly. METHODS: This descriptive cross-sectional study was conducted with 523 elderly individuals aged 65 years and over living in Erzurum province between July and November 2024. R programming language 4.1.3, G*Power 3.1, and SPSS-22 program we...

Hospital-Based Robotic Applications in Nursing Practice: A Scoping Review.

INTRODUCTION: The integration of robots into clinical practice requires careful consideration of their alignment with nursing workflows, patient needs...

Survivor Perspectives on Artificial Intelligence Integration in Breast Cancer Treatment: A Qualitative Study of Trust, Equity, and Application.

FUNDING: Funding (NIH #1OT2OD037972-01). OBJECTIVE: Artificial intelligence (AI) may enhance the efficiency and personalization of breast cancer (BC) ...

Automated Pharmacometric Model Development by Leveraging Low-Dimensional Neural ODEs and LASSO Regression.

Current pharmacometrics (PMX) model development is a manual process with iterative model building, fitting, and evaluation, which can be resource-inte...

Artificial intelligence in pediatric Wilms tumor imaging: diagnostic performance and the need for clinical oversight.

In-hospital mortality among patients with congenital heart disease undergoing noncardiac procedures: machine learning analysis of a multicentre study.

BACKGROUND: Improved survival for children with congenital heart disease (CHD) has resulted in an increasing number presenting for noncardiac procedur...

Detecting Adverse Events Following Acute Care Encounters among Veterans Prescribed Non-Steroidal Anti-Inflammatory Drugs.

OBJECTIVES: To model the occurrence of adverse events (AEs) among Veterans prescribed nonsteroidal anti-inflammatory drugs (NSAIDs) during emergency d...

Improving Emergency Care for Children With Medical Complexity: A Pragmatic Review.

Children with medical complexity (CMC) are defined by the presence of significant chronic health problems that affect multiple organ systems, often re...

Care Robots as Emerging Health Technologies: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Global aging and health care workforce shortages are increasing demand for therapeutic support among older adult and pediatric populations...

High Adoption, Higher Expectations: A Cross-Sectional Survey of Radiologist Engagement with Artificial Intelligence in the United Arab Emirates.

Artificial intelligence (AI) is poised to transform diagnostic radiology, yet data on its adoption and the perspectives of radiologists in the Middle ...

Predicting abnormal birth weight and identifying associated factors using machine learning in the Hararghe Health and Demographic Surveillance System, Ethiopia.

BACKGROUND: Birth weight is a reliable indicator of intrauterine growth and an important predictor of neonatal survival, growth, and long-term develop...

Generative Artificial Intelligence and 3D Printing in Craniomaxillofacial Deformities: A Narrative Review of Emerging Synergies.

Craniomaxillofacial deformities are primarily caused by congenital anomalies, trauma, or postoperative defects following tumor resection, involving bo...

Machine learning-based prediction model for adverse pregnancy outcomes in women with gestational diabetes mellitus.

AIMS/INTRODUCTION: Gestational diabetes mellitus (GDM) is one of the most frequent pregnancy complications. Investigating clinical risk factors for ad...

Understanding University Students' Experiences of Engaging With AI and Apps for Their Mental Health and Well-Being: Qualitative Study.

BACKGROUND: Fully automated digital technologies, such as artificial intelligence (AI) and apps, provide a particularly promising way to promote and s...

Deep Learning for Automated Infant Hip Ultrasound: Toward Robust Generalization across Disease Spectrum and Devices.

Automated radiographic shoulder balance assessment in scoliosis via deep learning.

The objective of this study was to develop an automated deep learning-based method for the assessment of shoulder balance in adolescent idiopathic sco...

From Data to Decision: Standardization, Validation, and Regulatory Readiness of AI-Driven Analytical Chemistry Workflows.

Artificial intelligence (AI) is fundamentally reshaping analytical chemistry by enabling automated data interpretation, intelligent method optimizatio...

Concepts of Facial Beauty: From Antiquity to the Era of AI-A Short Review.

Facial beauty has been cherished around the world and has captivated humans throughout history. Despite a series of attempts, however, it is still alm...

Comparative Outcomes of a Pediatric Walking Rehabilitation Robot Combined With Repetitive Transcranial Magnetic Stimulation in Children With Spastic Cerebral Palsy: Protocol for a Prospective Observational Study.

BACKGROUND: Cerebral palsy (CP) is a prevalent neurodevelopmental disorder in children, often leading to long-term motor impairments. Rehabilitation r...