An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU

OBJECTIVE: 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...

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Bibliographic Details
Published in:Crit Care Med
Main Authors: Nemati, Shamim, Holder, Andre, Razmi, Fereshteh, Stanley, Matthew D., Clifford, Gari D., Buchman, Timothy G.
Format: Artigo
Language:Inglês
Published: 2018
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Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC5851825/
https://ncbi.nlm.nih.gov/pubmed/29286945
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/CCM.0000000000002936
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