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. From these inputs the model produced paired arterial blood gases, first with the inspired O₂ fraction (FiO₂) adjusted to arterial saturation (SaO₂) = 0.90, and second with FiO₂ increased by 0.1. 'Stacked regressor' ML ensembles were trained/validated on 90% of this dataset. The remainder with shunt,

SUBMITTER: Morgan TJ 

PROVIDER: S-EPMC9188913 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature