Decision support of inspired oxygen selection based on Bayesian learning of pulmonary gas exchange parameters
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摘要
Objective:To investigate if the real-time Bayesian learning of physiological model parameters can be used to support and improve the selection of inspired oxygen fraction.
论文关键词：Decision support,Bayesian learning,Physiological modelling,Pulmonary gas exchange,Oxygen saturation
论文评审过程：Received 20 March 2004, Revised 23 July 2004, Accepted 24 July 2004, Available online 2 December 2004.
论文官网地址：https://doi.org/10.1016/j.artmed.2004.07.012
