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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Bibliografiset tiedot
Julkaisussa:Intensive Care Med
Päätekijät: 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.
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Springer Berlin Heidelberg 2020
Aiheet:
Systematic Review
Linkit: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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