FIGURE 2.

Feature importance of each variable in the best (gradient boosting machine) model. The x-axis is the relative importance of each variable measured as the relative quantity the prediction accuracy decreases when only the variable of interest is randomly permuted in the training set. These values are calculated by randomly permuting 1 variable at a time and measuring the decrease in accuracy of the model. Note that, in this case, the models do not explicitly divulge a positive or negative relationship of these variables to the outcome (eg, does increasing or decreasing age make liver transplantation more likely). ABG = pH. ABG, arterial blood gas; bili, bilirubin; BMI, body mass index; DCD, donor after circulatory death; MAP, mean arterial pressure; PF ratio, ratio of arterial blood concentration of oxygen over fraction of inspired oxygen.