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. 2023 Sep 26;76(6):540–549. doi: 10.4097/kja.23501

Fig. 2.

Fig. 2.

Boxplot of the feature importance from input candidates using the BorutaSHAP method. (A) Boxplot of the feature importance from input candidates (age, sex, weight, height, and existence of cuff) for predicting uncuffed ETT size using the BorutaSHAP method. (B) Boxplot of the feature importance from input candidates (age, sex, weight, height, and existence of cuff) for predicting cuffed ETT size using the BorutaSHAP method. (C) Boxplot of the feature importance from input candidates (age, sex, weight, height, and existence of cuff) for predicting uncuffed ETT depth using the BorutaSHAP method. (D) Boxplot of the feature importance from input candidates (age, sex, weight, height, and existence of cuff) for predicting cuffed ETT depth using the BorutaSHAP method. X-axis presents the input features and Y-axis shows the Z-score of whether each feature has an importance significantly lower than the threshold. Features confirmed important are presented in green (P < 0.05) and blue colors, while red color represents unimportant features (P < 0.05). The term ‘Shadow’ on the X-axis refers to shadow features generated by randomly permuting the dataset of each original feature. Then, the feature importance are computed in the original and the generated shadow features. ETT: endotracheal tube.