Cargando…
Using Explainable Machine Learning to Improve Intensive Care Unit Alarm Systems
Due to the continuous monitoring process of critical patients, Intensive Care Units (ICU) generate large amounts of data, which are difficult for healthcare personnel to analyze manually, especially in overloaded situations such as those present during the COVID-19 pandemic. Therefore, the automatic...
Autores principales: | González-Nóvoa, José A., Busto, Laura, Rodríguez-Andina, Juan J., Fariña, José, Segura, Marta, Gómez, Vanesa, Vila, Dolores, Veiga, César |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587076/ https://www.ncbi.nlm.nih.gov/pubmed/34770432 http://dx.doi.org/10.3390/s21217125 |
Ejemplares similares
-
Improving Intensive Care Unit Early Readmission Prediction Using Optimized and Explainable Machine Learning
por: González-Nóvoa, José A., et al.
Publicado: (2023) -
Two-Step Approach for Occupancy Estimation in Intensive Care Units Based on Bayesian Optimization Techniques
por: González-Nóvoa, José A., et al.
Publicado: (2023) -
Clinical Alarms in Intensive Care Units: Perceived Obstacles of Alarm Management and Alarm Fatigue in Nurses
por: Cho, Ok Min, et al.
Publicado: (2016) -
Alarms in the intensive care unit: how can the number of false alarms be reduced?
por: Chambrin, Marie-Christine
Publicado: (2001) -
Reduction of false alarms in the intensive care unit using an optimized machine learning based approach
por: Au-Yeung, Wan-Tai M., et al.
Publicado: (2019)