Pediatrics

Predicting COVID-19 severity using machine learning: the role of clinical parameters, blood groups, and vaccination status across age groups.

OBJECTIVES: COVID-19 has had strong impacts on both global health systems and economies. Therefore, ...

Explainable machine learning for the early differentiation of pediatric bronchopneumonia using routine laboratory parameters.

OBJECTIVE: Early differentiation of pediatric acute respiratory infections in outpatient and emergen...

Artificial Intelligence in Pharmaceutical Care: Transforming Drug Discovery, Development, and Patient-care Delivery.

The integration of artificial intelligence (AI) into pharmaceutical care represents a paradigm shift...

Can Machine Learning Transform the Diagnostic Approach to Congenital Disorders of Adrenal Steroidogenesis?

Bridging the global Parkinson's divide: Technology as a structural solution for equitable and brain health-integrated care.

Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder worldwide, with projectio...

Multi-method statistical signal aggregation with machine learning for severity classification of neonatal adverse drug reactions.

Neonates represent one of the most pharmacologically vulnerable patient populations, yet they remain...

The role and application of task-state fNIRS in identifying biomarkers in children and adolescents with ADHD: a systematic review.

Attention Deficit Hyperactivity Disorder (ADHD), a prevalent neurodevelopmental condition, urgently ...

Two systems, two timelines: Computational evidence for dissociable development in inhibitory control across childhood and adolescence.

This study examined inhibitory control development across two samples of Chinese children: a cross-s...

Exploring the Experiences of Moderators From an Asynchronous Online Dementia Support Forum: Qualitative Interview Study.

BACKGROUND: Asynchronous online forums provide flexible, accessible peer support for many people liv...

Feasibility of Tailoring Artificial Intelligence-Assisted Ambient Scribes for Intensive Care Unit Rounds: Algorithm Development and Validation.

BACKGROUND: The increasing documentation burden on physicians is a significant contributor to burnou...

AI Meets Attitudes: Cross-Sectional Quantitative Study of COVID-19 Vaccine Hesitancy in Alaska's Diverse Communities.

BACKGROUND: The global COVID-19 vaccine rollout faces challenges from persistent hesitancy, especial...

Dual-Mode Nucleation and Dynamic Alloying of Silicon on Ag(111).

Silicon growth on Ag(111) is a prototypical system for exploring silicene-like monolayers and comple...

Machine learning and mobile sensing for naturalistic infant behavior (0-36 months): A comprehensive review and research agenda.

The recent rapid development of mobile and wearable sensing technologies and computational modeling ...

AI-Based Longitudinal Scoliosis Monitoring on EOS Whole-Spine Radiographs in a Pediatric to Young Adult Cohort.

RATIONALE AND OBJECTIVES: Manual Cobb angle measurement can exhibit high interrater variability, pot...

Pediatric fracture classification in plain radiographs using EfficientNetV2 with proximal policy optimization fine-tuning.

Pediatric fracture detection in plain radiographs presents distinct clinical challenges due to the p...

A multimodal machine learning framework outperforms traditional performance metrics for predicting elite national ranking attainment in adolescent sprinters.

Traditional talent identification in sprinting relies heavily on chronological performance metrics, ...

PANDA pediatric arousal neural detection architecture.

We developed and validated PANDA, a deep-learning model for pediatric arousal detection in polysomno...

Cross-Center Online Generalization Algorithm with Unadversarial Consistency for Fetal Heart Ultrasound View Recognition.

Fetal congenital heart disease (FCHD) remains a leading cause of infant mortality globally, yet the ...

Comparative Efficacy of Trained Versus Untrained Generative Artificial Intelligence Platforms in Providing Case-Based Multiple-Choice Questions on Traumatic Dental Injuries in the Pediatric Dentistry Curriculum: A Cross-Sectional Study.

BACKGROUND/AIM: To determine the comparative efficacy of trained versus untrained generative artific...

Head and Neck Free Flap Reconstruction: Current Landscape and Emerging Technologies.

OBJECTIVE: To synthesize contemporary developments in head and neck oncologic free flap reconstructi...

Widely available, general-purpose generative AI applications for radiology education: determining the teaching quality of synthetic pediatric neuroradiology images.

BACKGROUND: Artificial intelligence (AI) is increasingly incorporated into medical education. Widely...