Pediatrics

Development of an artificial intelligence-assisted system for tracheal intubation using a video laryngoscope in infants and neonates.

BACKGROUND: The larynx of infants and neonates is occasionally challenging to identify using video l...

Death One Hour After Terminal Extubation in Children: Validation of a Machine Learning Model to Predict Cardiac Death After Withdrawal of Life-Sustaining Treatment in a Multicenter Cohort, 2009-2021.

OBJECTIVES: In the PICU, predicting death within 1 hour after terminal extubation (TE) is valuable i...

Novel Application of Connectomics to the Surgical Management of Pediatric Arteriovenous Malformations.

Introduction The emergence of connectomics in neurosurgery has allowed for construction of detailed ...

In silico & in vitro approaches suggest osteoclastogenesis induction underlying fractures in Entrectinib-treated children.

Entrectinib, a potent, CNS-active, TRK and ROS1 inhibitor is associated with occurrence of bone frac...

Comprehensive analysis and experimental validation of BST1 as a novel diagnostic biomarker for pediatric sepsis using multiple machine learning algorithms.

Bone marrow stromal cell antigen-1 (BST1) expression is elevated in a variety of human diseases, but...

Currently Available Large Language Models Are Moderately Effective in Improving Readability of English and Spanish Patient Education Materials in Pediatric Orthopaedics.

INTRODUCTION: Patient education materials (PEMs) consistently exceed the recommended sixth-grade rea...

N.U.R.S.E.S. embracing artificial intelligence: A guide to artificial intelligence literacy for the nursing profession.

Artificial intelligence (AI) is reshaping health care, making AI literacy vital for nursing professi...

Harnessing Generative Artificial Intelligence in Pediatric Anesthesia: Enhancing Learning, Patient Care, and Family Communication.

Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.

OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates...

Neural network-based multi-task learning to assist planning of posterior spinal fusion surgery for adolescent idiopathic scoliosis.

PURPOSE: Posterior spinal instrumentation and fusion (PSF) is the gold standard for severe adolescen...

A Comparative Assessment of Large Language Models in Pediatric Dialysis: Reliability, Quality and Readability.

INTRODUCTION: This study evaluated the reliability, quality, and readability of ChatGPT (OpenAI, San...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

: Early identification and timely preventive interventions play an essential role for improving the ...

Physiological Response of Tissue-Engineered Vascular Grafts to Vasoactive Agents in an Ovine Model.

Tissue-engineered vascular grafts (TEVGs) are emerging as promising alternatives to synthetic grafts...

AI in Medical Questionnaires: Innovations, Diagnosis, and Implications.

This systematic review aimed to explore the current applications, potential benefits, and issues of ...

Axial Skeletal Assessment in Osteoporosis Using Radiofrequency Echographic Multi-spectrometry: Diagnostic Performance, Clinical Utility, and Future Directions.

Osteoporosis, a prevalent skeletal disorder, necessitates accurate and accessible diagnostic tools f...

Editor's view: Value of information in the 21st century - examples from science, medicine, policy, media, and markets.

This editorial explores the concept of the 'value of information' in the 21st century through five d...

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat.

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential...

Adolescent lumbar disc herniation: etiology, diagnosis, and treatment options.

Adolescent lumbar disc herniation (ALDH) is a type of disease with a much lower incidence than adult...

Leveraging machine learning to identify determinants of zero utilization of maternal continuum of care in Ethiopia: Insights from SHAP analysis and the 2019 mini DHS.

Ensuring complete utilization of maternal continuum of care is essential for reducing maternal and n...

Advances in vaccine adjuvant development and future perspectives.

Use of highly purified antigens to improve vaccine safety has led to reduced immunogenicity and effi...

Machine learning model for daily prediction of pediatric sepsis using Phoenix criteria.

BACKGROUND: Early sepsis diagnosis is essential for initiating prompt treatment, preventing the prog...