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Fig. 5 | Journal of Translational Medicine

Fig. 5

From: Prediction of acute kidney injury after cardiac surgery: model development using a Chinese electronic health record dataset

Fig. 5

SHAP dependence plot of the random forest model. Each panel demonstrates that each feature affects the output of the random forest prediction model. The x-axis represents the raw values of each feature and the y-axis indicates the SHAP values of features. When the SHAP value of a specific feature exceeds zero, it indicates an increased risk of acute renal injury. CVP: central venous pressure; CUF: conventional ultrafiltration; LDH: lactic dehydrogenase; NLR: neutrophil to lymphocyte ratio; Scr: serum creatinine; UA: uric acid; HDL: high-density lipoprotein

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Journal of Translational Medicine

ISSN: 1479-5876

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