… population to remain relevant. Additional limitations that are specific to a pediatric population
include the smaller patient population … Within that smaller population, there is also greater …

… for this particularly vulnerable population and avoid excessive numbers of false alarms. Our
machine learning algorithm outperforms the PELOD-2 and pediatric SIRS scoring systems, …

… Some studies investigated the readmissions in general population or with … machine learning
techniques to predict potentially avoidable 30-day readmission on the pediatric population. …

… (LTG), and levetiracetam (LEV) in a pediatric population using nonlinear mixed-effect
modeling, while machine learning (ML) algorithms were applied to identify any relationships …

… of machine learning (ML) to address population health … associated with its use at a population
level. The review concludes by … This review explores the potential role of machine learning …

Objectives: To explore whether machine learning applied to pediatric critical care data could
discover medically pertinent information, we analyzed clinically collected electronic medical …

… The study is concerned with the pediatric population, however, the definition for pediatric in
our study included only term patients, excluding all premature populations. A limitation of the …

… in the Singapore population compared to that … population comprised of young children
presented after low mechanism falls. This likely accounted for the low event rate in our population …

… pediatric patients [7], finding lower sensitivity in the pediatric population than in the adult
population… first ones applying machine learning techniques to all-cause pediatric readmissions. …

… population as a model built on pediatric data alone. Importantly, a machine learning
method … with combined adult and pediatric data to a pediatric population. These findings are …