Reduction of false alarms in the intensive care unit using an optimized machine learning based approach

This work attempts to reduce the number of false alarms generated by bedside monitors in the intensive care unit (ICU), as a majority of current alarms are false. In this study, we applied methods that can be categorized into three stages: signal processing, feature extraction, and optimized machine...

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Detalles Bibliográficos
Autores principales: Au-Yeung, Wan-Tai M., Sahani, Ashish K., Isselbacher, Eric M., Armoundas, Antonis A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728371/
https://www.ncbi.nlm.nih.gov/pubmed/31508497
http://dx.doi.org/10.1038/s41746-019-0160-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728371/
https://www.ncbi.nlm.nih.gov/pubmed/31508497
http://dx.doi.org/10.1038/s41746-019-0160-7

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