Development and clinical impact assessment of a machine-learning model for early prediction of late-onset sepsis.

Background And Aim: Preterm infants are prone to neonatal infections such as late-onset sepsis (LOS). The consequences of LOS can be severe and potentially life-threatening. Unfortunately, LOS often presents with unspecific symptoms, and early screening laboratory tests have limited diagnostic value and are often late.