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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Detalhes bibliográficos
Publicado no: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.
Formato: Artigo
Idioma:Inglês
Publicado em: Springer Berlin Heidelberg 2020
Assuntos:
Systematic Review
Acesso em linha: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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