Viscosity Prediction in a Physiologically Controlled Ventricular Assist Device.
Journal:
IEEE transactions on bio-medical engineering
PMID:
29993524
Abstract
OBJECTIVE: We present a novel machine learning model to accurately predict the blood-analog viscosity during support of a pathological circulation with a rotary ventricular assist device (VAD). The aim is the continuous monitoring of the hematocrit (HCT) of VAD patients with the benefit of a more reliable pump flow estimation and a possible early detection of adverse events, such as bleeding or pump thrombosis.