Pediatrics

Differentiating septic arthritis from non-infectious inflammatory causes of acute monoarticular arthritis in children: A machine learning approach based on routine laboratory tests.

OBJECTIVE: Acute monoarthritis in children poses a diagnostic challenge, particularly in distinguishing septic arthritis from non-infectious inflammatory causes. Delayed or incorrect diagnosis may lead to serious complications or inappropriate treatment. This study aims to develop and validate machine learning (ML) models for distinguishing septic arthritis from non-infectious inflammatory arthrit...

GraphGDel: Constructing and Learning Graph Representations of Genome-Scale Metabolic Models for Growth-Coupled Gene Deletion Prediction.

In genome-scale constraint-based metabolic models, gene deletion strategies are essential for achieving growth-coupled production, where cell growth and target metabolite synthesis occur simultaneously. Despite the inherently networked nature of genome-scale metabolic models, existing computational approaches rely primarily on sequential data and lack graph representations that capture their compl...

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on...

Automated early preterm detection using hybrid multimodal attention network with gated fusion.

Preterm birth is a major pregnancy complication associated with increased maternal and neonatal risks, making early detection of labor essential. Elec...

Prospective Validation of Multi-week Inpatient Census Forecasting for Pediatric HSCT and Cellular Therapy.

BACKGROUND: Accurate inpatient census forecasting is important for cell therapy and blood and marrow transplantation (BMT) programs because bed capaci...

Prediction of bronchopulmonary dysplasia seven days after birth using respiratory and oxygenation timeseries with machine learning.

BACKGROUND: Accurate prediction of bronchopulmonary dysplasia (BPD) development would allow targeted early treatment. This study aims to develop a mac...

The future of pediatric gene therapy: CRISPR-Cas9, AI, and personalized medicine.

The future of pediatric gene therapy is being fundamentally reshaped by the convergence of CRISPR-Cas9 genome editing, artificial intelligence (AI), a...

A CT-based deep learning model for the automated risk stratification of refractory Mycoplasma pneumoniae pneumonia in children.

BACKGROUND: The accurate identification of children with refractory Mycoplasma pneumoniae pneumonia (RMPP) remains challenging. This study aimed to de...

Earlier medically ready for discharge date entry associated with lower unnecessary bed days.

BACKGROUND: Discharge planning plays a critical role in managing patient hospital length of stay. We report on the implementation of a program in a la...

Medical student reliance on artificial intelligence in nephrology education.

BACKGROUND: Large language models such as ChatGPT are increasingly used in medical education and may influence student learning and decision-making. D...

The illusion of competence: Evaluating the clinical reasoning of large language models in pediatric gastroenterology.

OBJECTIVE: To evaluate the diagnostic accuracy and clinical reasoning of three frontier large language models (LLMs) across standardized pediatric gas...

Automatic preprocessing pipeline for individual-plant level (IPL) soybean growth monitoring through UAV multisource imagery.

Orthoimagery derived from unmanned aerial vehicles (UAVs) has become a valuable data source for crop-growth monitoring. Individual plant-level (IPL) i...

Thinking about the Impact of Artificial Intelligence on U.S. Health Care Costs and Spending Growth.

This article critically examines the potential impacts of artificial intelligence (AI) on prices, total spending, and the rate of spending growth in t...

On-demand growth of semiconductor heterostructures guided by physics-informed machine learning.

Developing tailored heterostructures on demand is essential to meet the growing needs of semiconductor devices. However, traditional methods remain co...

Development and validation of a vision transformer model for radiographic assessment of pediatric humeroradial joint alignment.

BACKGROUND: Whether the radiographic assessments of pediatric anatomical (A-HRJA) and nonanatomical humeroradial joint alignment (NA-HRJA) among pedia...

Comparative Interpretation of Pediatric Electrocardiograms by Large Language Models and a Pediatrician.

OBJECTIVE: Large language models (LLMs) have been explored for clinical applications, yet their reliability in pediatric electrocardiogram (ECG) inter...

Smart nanoparticle vaccines integrate nanotechnology artificial intelligence and immunoengineering for precision immunization.

The rise of multidrug-resistant microbes, rapidly evolving viruses, and recurring pandemics underscores the urgent need for advanced vaccine technolog...

Research progress on detection technologies for Mycoplasma pneumoniae.

Mycoplasma pneumoniae (M. pneumoniae) is a primary pathogen responsible for community-acquired pneumonia (CAP), particularly prevalent among children ...

Development and Validation of a Simplified Martin-Hopkins LDL-C Equation Using Machine Learning.

IMPORTANCE: Although the Martin-Hopkins equation is widely validated and used to estimate low-density lipoprotein cholesterol (LDL-C) for clinical car...

Detection of bronchopulmonary dysplasia in infants and prediction of school-age lung function from tidal breathing data using recurrent neural networks.

Objective.To test whether machine learning (ML) models trained on tidal breathing flow time series can discriminate between individuals with and witho...