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Fig. 3 | European Journal of Medical Research

Fig. 3

From: Interpretable machine learning model for early prediction of 28-day mortality in ICU patients with sepsis-induced coagulopathy: development and validation

Fig. 3

The interpretation of the XGBoost model. A Feature importance ranking based on SHAP values. The position on the Y-axis implied the importance ranking, and the X-axis reflected the association between each value of features and the corresponding SHAP value. B The importance ranking of included features according to the mean (|SHAP value|). SOFA sequential organ failure assessment, RDW red blood cell distribution width, MCV mean corpuscular volume, BUN blood urea nitrogen, MBP mean blood pressure, WBC white blood cell, MCHC mean corpuscular hemoglobin concentration

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