DocumentCode :
3684939
Title :
Next generation patient monitor powered by in-silico physiology
Author :
Dimitar Baronov;Michael McManus;Evan Butler;Douglas Chung;Melvin C. Almodovar
Author_Institution :
Etiometry Inc. Boston, MA, United States
fYear :
2015
Firstpage :
4447
Lastpage :
4453
Abstract :
The goal of this paper is to introduce a next generation patient monitoring technology that relies on objective and continuous data analytics to alleviate the data overload in the critical care unit. The technology provides the foundation for increasing the consistency and efficacy of data use in clinical practice and improving outcomes. This paper presents results for applying the approach to the hemodynamic monitoring of infants immediately following cardiac surgery and demonstrates its efficacy of estimating the probability of inadequate systemic oxygen delivery, which is an essential risk attribute in the management of critically ill patients.
Keywords :
"Biomedical monitoring","Uncertainty","Physiology","Blood","Computational modeling","Risk management","Estimation"
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN :
1094-687X
Electronic_ISBN :
1558-4615
Type :
conf
DOI :
10.1109/EMBC.2015.7319382
Filename :
7319382
Link To Document :
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