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Feature importance in the GRU-D recurrent neural network model as defined by the average drop in the area under the receiver operator characteristic curve (with 95% CI) when each feature is individually removed from the analysis. The top 5 features are seen to be age, Charlson comorbidity index, minimum oxygen saturation, fibrinogen levels, and serum iron levels. AUROC: area under the receiver operator characteristic.
