Pulmonary gas exchange evaluated by machine learning a computer simulation

Abstract

Using computer simulation we investigated whether machine learning (ML) analysis of selected ICU monitoring data can quantify pulmonary gas exchange in multi-compartment format. A 21 compartment ventilation/perfusion (V/Q) model of pulmonary blood flow processed 34,551 combinations of cardiac output, hemoglobin concentration, standard P50, base excess, VO2 and VCO2 plus three model-defining parameters: shunt, log SD and mean V/Q.