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. 2022 May 6;12(5):756. doi: 10.3390/jpm12050756

Table 6.

Overall importance ranking of each risk factor in predicting bleeding based on RF and XGBoost.

Risk Factors Average Ranking of 10 Times RF Average Ranking of 10 Times XGBoost Average Ranking of the 2 Models Final Ranking in Predicting Bleeding
Age 1 1.3 1.15 1
Kidney function 3.2 3.5 3.35 2
Smoking 2.1 4.7 3.4 3
Previous bleeding history 4.7 2.4 3.55 4
Concomitant use of drugs 4.8 5 4.9 5
Medicine dosage (dabigatran) 7 6.7 6.85 6
BMI 5.2 9.6 7.4 7
History of myocardial infarction 9.2 6.1 7.65 8
History of congestive heart failure 10.1 10.3 10.2 9
Ethnicity 9.1 12.2 10.65 10
Sex 10.8 11.3 10.55 11
History of diabetes mellitus 12.8 11.5 12.15 12
Previous stroke history 11 14.2 12.6 13
Hypertension history 14 12.6 13.3 14
Body weight 15 12.3 13.65 15
History of systemic embolism 16 13 14.5 16
Liver function abnormality 17 17 17 17
Anemia 18 17.4 17.7 18

Abbr.: RF, random forest; XGBoost, eXtreme gradient boosting; BMI, body mass index.