Prediction of Late-Onset Sepsis in Preterm Infants Using Monitoring Signals and Machine Learning

Abstract

Information from routine patient monitoring can be used to predict sepsis. Specifically, this study shows that a combination of electrocardiogram-based, respiration-based, and motion-based features enables the prediction of late-onset sepsis hours before the clinical crash moment.