We created an online calculator using machine learning (ML) algorithms to impute the partial pressure of oxygen (PaO)/fraction of delivered oxygen (FiO) ratio using the non-invasive peripheral saturation of oxygen (SpO) and compared the accuracy of the ML models we developed to published equations. We generated three ML algorithms (neural network, regression, and kernel-based methods) using seven clinical variable features (N = 9900 ICU events) and subsequently three features (N = 20,198 ICU events) as input into the models. Data from mechanically ventilated ICU patients were obtained from the publicly available Medical Information Mart for Intensive Care (MIMIC III) database and used for analysis.
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