Fig. 5
From: Prediction of the development of acute kidney injury following cardiac surgery by machine learning
SHAP summary plot of the top 20 features of the RF model. The higher the SHAP value of a feature, the higher the probability of postoperative acute kidney injury development. A dot is created for each feature attribution value for the model of each patient, and thus one patient is allocated one dot on the line for each feature. Dots are colored according to the values of features for the respective patient and accumulate vertically to depict density. Red represents higher feature values, and blue represents lower feature values. Abbreviations: pRBC, packed red blood cell; HGB, hemoglobin; eGFR, estimated glomerular filtration rate; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; LV, left ventricular; MAP, mean arterial pressure; PCA, principal component analysis; SBP, systolic blood pressure; HR, heart rate; RV, real variability; HTN, hypertension; PLT, platelet; BMI, body mass index