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Reducing False Arrhythmia Alarms Using Different Methods of Probability and Class Assignment in Random Forest Learning Methods

The literature indicates that 90% of clinical alarms in intensive care units might be false. This high percentage negatively impacts both patients and clinical staff. In patients, false alarms significantly increase stress levels, which is especially dangerous for cardiac patients. In clinical staff...

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Detalhes bibliográficos
Publicado no:Sensors (Basel)
Main Authors: Gajowniczek, Krzysztof, Grzegorczyk, Iga, Ząbkowski, Tomasz
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6479538/
https://ncbi.nlm.nih.gov/pubmed/30986930
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19071588
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