2022
DOI: 10.36227/techrxiv.19982840
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A Continuous Late-Onset Sepsis Prediction Algorithm for Preterm Infants using Multimodal Physiological Signals from a Patient Monitor

Abstract: <p>This study describes a machine learning algorithm based on multimodal signals obtained from a regular clinical patient monitor to predict late-onset sepsis (LOS) in preterm infants in a neonatal intensive care unit (NICU). The algorithm uses features that contain information on heart rate variability (HRV), respiration, and motion, based on continuously measured physiological waveforms including electrocardiogram (ECG) and chest impedance (CI). In this study, 127 preterm infants were included, of whom… Show more

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