Pediatrics

Data subdivision approach enhances machine learning-based mortality prediction in pediatric ICU patients.

OBJECTIVE: To evaluate machine learning-based models for predicting all-cause mortality in pediatric ICU patients using comprehensive biochemical panels, with a focus on addressing missing data and class imbalance. MATERIALS AND METHODS: A retrospective analysis was performed on a publicly available PICU dataset comprising 8,629 patients aged 28 days to 18 years. Twenty-two biochemical variables m...

Use of Artificial Intelligence in Screening for Adolescent Idiopathic Scoliosis: A Scoping Review.

INTRODUCTION: Adolescent idiopathic scoliosis (AIS) screening remains controversial, particularly regarding its effectiveness and cost-effectiveness in population settings. The Scoliosis Research Society - AIS screening (SRS-AIS) is simple, reliable, and widely accepted in clinical practice. With the emerging of artificial intelligence (AI) in medical screening, AI-based approaches have been propo...

Artificial Intelligence in Neonatal Hip Ultrasound: A Scoping Review of Methods and Clinical Evidence.

BACKGROUND: Developmental dysplasia of the hip (DDH) is among the most common musculoskeletal disorders in infants. Ultrasound, especially the Graf me...

Predicting psychopathology symptom trajectories using machine learning: a 33-year prospective study.

BACKGROUND: While previous literature has established a link between psychopathology symptom trajectories and psychosocial risk, most studies have not...

The gut microbiome in preterm infants: development, dysbiosis, and disease implications.

SUMMARYPreterm infants face a unique trajectory of gut microbiome assembly, shaped by the convergence of physiological immaturity, necessary clinical ...

From Ambient Assistance to Data-Driven Precision in AI-Enabled Alzheimer's Care (2004-2025): A Bibliometric Perspective.

BACKGROUND AND OBJECTIVES: Population aging and the rising prevalence of Alzheimer's Disease and Related Dementias (AD/ADRD) have created an urgent ne...

Heterogeneous developmental trajectories and predictors of self-harm in early adolescence: A machine learning study.

BACKGROUND: Although prior studies have examined developmental trajectories of adolescent self-harm in terms of frequency and severity, a fundamental ...

Multi-omics body-fluid biomarkers in immunoglobulin a nephropathy: Analytical Validation, standardization, and clinical chemistry translation of diagnostic and prognostic Analytes.

IgA nephropathy (IgAN) is the most prevalent primary glomerulonephritis worldwide. Although optimized supportive therapy is administered to these pati...

Loneliness and social isolation at the emergency department: a scoping review protocol.

INTRODUCTION: Loneliness and social isolation are critical public health issues linked to significant adverse health outcomes and increased healthcare...

Physical therapy using digital therapeutics in infants with congenital muscular torticollis: a pilot study.

Congenital muscular torticollis (CMT) is a common musculoskeletal problem associated with unilateral sternocleidomastoid muscle stiffness. We evaluate...

Predicting survival in extremely preterm infants: A multicenter machine learning study from Spain.

BACKGROUND AND OBJECTIVE: Accurately predicting outcomes in extremely preterm infants remains a major challenge in neonatology. Traditional scores suc...

Chronic Total Occlusion Recanalization in a 14-Year-Old Girl With Pseudoxanthoma Elasticum: IVUS-Guided Stentless Strategy.

BACKGROUND: Pseudoxanthoma elasticum (PXE) is a hereditary disorder causing progressive arterial mineralization that may cause premature coronary dise...

Leveraging administrative health records and machine learning for population-level prediction of preterm birth.

BACKGROUND: Preterm birth, defined as delivery before 37 weeks of gestation, is a major cause of neonatal morbidity and mortality and places a substan...

Children and adolescents' views on artificial intelligence in pediatric healthcare: a qualitative focus group study.

BACKGROUND: The increased use of artificial intelligence (AI) in healthcare, including pediatrics, offers significant opportunities for improving qual...

Data After Death: Post-Mortem Ethics of Burn Patient Records and Images.

Burn care frequently relies on extensive documentation, including graphic photographic images and detailed clinical records. While these materials are...

A Review of the Australian MRI Linac Program: From Pie in the Sky to Research Milestone.

The Australian Magnetic Resonance Imaging (MRI) Linear Accelerator program (MRI linac) was a major research project that aimed to build and test a uni...

Improving Trauma Triage Accuracy with Large Language Models: A Comparison to Human Expert Decisions.

BACKGROUND: Accurate prehospital trauma triage and communication determine morbidity, mortality, and system efficiency. Advancements in large language...

A 10-year analysis of the united network for organ sharing registry: Insights from machine learning to prevent pediatric waitlist deaths.

Artificial Intelligence in Self-Management of Gestational Diabetes Mellitus: A Systematic Review.

The prevalence of gestational diabetes mellitus (GDM) continues to rise, necessitating reliable and effective self-management strategies to improve ma...

Knowledge-Augmented Large Language Model for Multimodal Electronic Health Record-Based Risk Prediction: Development and Validation Study.

BACKGROUND: Accurate clinical outcome prediction using electronic health records (EHRs) is crucial for patient care and resource allocation. EHRs incl...