Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial

INTRODUCTION: Several methods have been developed to electronically monitor patients for severe sepsis, but few provide predictive capabilities to enable early intervention; furthermore, no severe sepsis prediction systems have been previously validated in a randomised study. We tested the use of a...

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Detalles Bibliográficos
Autores principales: Shimabukuro, David W, Barton, Christopher W, Feldman, Mitchell D, Mataraso, Samson J, Das, Ritankar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Critical Care
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5687546/
https://www.ncbi.nlm.nih.gov/pubmed/29435343
http://dx.doi.org/10.1136/bmjresp-2017-000234

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5687546/
https://www.ncbi.nlm.nih.gov/pubmed/29435343
http://dx.doi.org/10.1136/bmjresp-2017-000234

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