An interpretable machine learning model for accurate prediction of sepsis in the ICU
Objectives: Sepsis is among the leading causes of morbidity, mortality, and cost overruns in
critically ill patients. Early intervention with antibiotics improves survival in septic patients.
However, no clinically validated system exists for real-time prediction of sepsis onset. We
aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early
prediction of sepsis. Design: Observational cohort study. Setting: Academic medical center
from January 2013 to December 2015. Patients: Over 31,000 admissions to the ICUs at two …
critically ill patients. Early intervention with antibiotics improves survival in septic patients.
However, no clinically validated system exists for real-time prediction of sepsis onset. We
aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early
prediction of sepsis. Design: Observational cohort study. Setting: Academic medical center
from January 2013 to December 2015. Patients: Over 31,000 admissions to the ICUs at two …
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