Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data

Abstract

Machine learning models can identify infants with sepsis in the NICU hours prior to clinical recognition. Learning curves indicate model improvement may be achieved with additional training examples. Additional input features may also improve performance. Further research is warranted to assess potential performance improvements and clinical efficacy in a prospective trial.