The number of microbubbles generated during cardiopulmonary bypass can be estimated using machine learning from suction flow rate, venous reservoir level, perfusion flow rate, hematocrit level, and blood temperature

The number of microbubbles generated during cardiopulmonary bypass can be estimated using machine learning from suction flow rate, venous reservoir level, perfusion flow rate, hematocrit level, and blood temperature 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Abstract:

Microbubbles (MBs) are known to occur within the circuits of cardiopulmonary bypass (CPB) systems, and higher-order dysfunction after cardiac surgery may be caused by MBs as well as atheroma dispersal associated with cannula insertion. As complete MB elimination is not possible, monitoring MB count rates is critical. We propose an …

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