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, log SD, and mean ‘held back’ formed the test-set. ‘Two-Point’ ML estimates of shunt, log SD and mean utilized data from both FiO₂ settings. ‘Single-Point’ estimates used only data from SaO₂ = 0.90. From 3454 test gas exchange scenarios, two-point shunt, log SD and mean estimates produced linear regression models versus true values with slopes ~ 1.00, intercepts ~ 0.00 and R² ~ 1.00. Kernel density and Bland–Altman plots confirmed close agreement. Single-point estimates were less accurate: R² = 0.77–0.89, slope = 0.991–0.993, intercept = 0.009–0.334. ML applications using blood gas, indirect calorimetry, and cardiac output data can quantify pulmonary gas exchange in terms describing a 20 compartment V/Q model of pulmonary blood flow. High fidelity reports require data from two FiO₂ settings.

我们使用计算机模拟研究了所选 ICU 监测数据的机器学习 (ML) 分析是否可以量化多隔室格式的肺部气体交换。肺血流的 21 室通气/灌注 (V/Q) 模型处理了心输出量、血红蛋白浓度、标准 P50、碱过剩、VO 2 和_VCO 2_的34,551 种组合以及三个模型定义参数：分流、log SD 和平均值V/Q。根据这些输入，模型产生了成对的动脉血气，首先是将吸入的 O2_分数(FiO2 ₎调整为动脉饱和度 (SaO2 ₎ = 0.90，然后是_FiO2增加了 0.1。'Stacked regressor' ML 集成在此数据集的 90% 上进行了训练/验证。具有分流、对数 SD 和均值“阻止”的其余部分构成了测试集。两种 FiO ₂设置的分流、log SD 和平均利用数据的“双点”ML 估计。“单点”估计仅使用来自 SaO ₂  = 0.90 的数据。从 3454 种测试气体交换场景、两点分流、对数 SD 和平均估计产生了线性回归模型与真实值，斜率 ~ 1.00，截距 ~ 0.00 和 R 2 ~ ^1.00  。核密度和 Bland-Altman 图证实了非常一致。单点估计不太准确：R ² = 0.77–0.89，斜率 = 0.991–0.993，截距 = 0.009–0.334。使用血气、间接量热法和心输出量数据的 ML 应用程序可以根据描述肺血流的 20 室 V/Q 模型来量化肺气体交换。高保真报告需要来自两个 FiO ₂设置的数据。