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A vasopressor advisability index for hemodynamic monitoring
Wei Zong1, Mohammed Saeed, Larry Nielsen
1Philips Healthcare, Andover, MA, USA.
Abstract:
To predict the need for vasopressor therapy, arterial blood pressure and heart rate are taken as inputs to a fuzzy-logic based algorithm that generates a 'vasopressor advisability index'. We evaluated the algorithm against patient records from a large intensive care database. The algorithm achieved a sensitivity of 69.7% and a specificity of 84.2% on a test set that was independent of the training set used.
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