Fig. 7: SHAP based feature importance for 1-year mortality. | npj Digital Medicine

Fig. 7: SHAP based feature importance for 1-year mortality.

From: Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms

Fig. 7

a SHAP analysis of the XGBoost models with ECG measurements, age, sex showed that higher age, lower RR interval, horizontal QRS axis (conditional effect), higher Bazett’s rate-corrected QT interval, male sex and lower PR interval contributed the most to the 1-year mortality. b The addition of lab features highlighted contributions of lower hemoglobin, lower glomerular filtration rate (GFR), lower troponin I, higher creatinine, very high or low sodium and high potassium. The description of ECG measurements is provided in the Supplementary Table 5.

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