Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy

PURPOSE: Early clinical recognition of sepsis can be challenging. With the advancement of machine learning, promising real-time models to predict sepsis have emerged. We assessed their performance by carrying out a systematic review and meta-analysis. METHODS: A systematic search was performed in Pu...

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Bibliographic Details
Published in:Intensive Care Med
Main Authors: Fleuren, Lucas M., Klausch, Thomas L. T., Zwager, Charlotte L., Schoonmade, Linda J., Guo, Tingjie, Roggeveen, Luca F., Swart, Eleonora L., Girbes, Armand R. J., Thoral, Patrick, Ercole, Ari, Hoogendoorn, Mark, Elbers, Paul W. G.
Format: Artigo
Language:Inglês
Published: Springer Berlin Heidelberg 2020
Subjects:
Systematic Review
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC7067741/
https://ncbi.nlm.nih.gov/pubmed/31965266
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s00134-019-05872-y
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