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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Detalles Bibliográficos
Autores principales: Gajowniczek, Krzysztof, Grzegorczyk, Iga, Ząbkowski, Tomasz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479538/
https://www.ncbi.nlm.nih.gov/pubmed/30986930
http://dx.doi.org/10.3390/s19071588

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479538/
https://www.ncbi.nlm.nih.gov/pubmed/30986930
http://dx.doi.org/10.3390/s19071588

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