Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The adoption of the Phoenix sepsis criteria eliminated the Systemic Inflammatory Response Syndrome criteri...
Looking at caregivers' faces is important for early social development, and there is a concomitant increase in neural correlates of attention to familiar versus novel faces in the first 6 months. However, by 12 months of age brain responses may not d...
PURPOSE: Data on end-of-life care (EOLC) quality, assessed through evidence-based quality measures (QMs), are difficult to obtain. Natural language processing (NLP) enables efficient quality measurement and is not yet used for children with serious i...
Studies in health technology and informatics
Aug 22, 2024
Emergency departments (EDs) are pivotal in detecting child abuse and neglect, but this task is often complex. Our study developed a machine learning model using structured and unstructured electronic health record (EHR) data to predict when children ...
Purpose To develop, externally test, and evaluate clinical acceptability of a deep learning pediatric brain tumor segmentation model using stepwise transfer learning. Materials and Methods In this retrospective study, the authors leveraged two T2-wei...
BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred immediately to secondary care to avoid life-threatening diabetic ketoacidosis. However, early recognition of children with type 1 diabetes is challengin...
Cerebral cortex (New York, N.Y. : 1991)
May 2, 2024
Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and...
OBJECTIVE: This study aimed to use machine learning to evaluate the risk factors of seizures and develop a model and nomogram to predict seizures in children with coronavirus disease 2019 (COVID-19).
Background Commonly used pediatric lower extremity growth standards are based on small, dated data sets. Artificial intelligence (AI) enables creation of updated growth standards. Purpose To train an AI model using standing slot-scanning radiographs ...