Table 2.

AUC comparison of XGBoost vs. clinical scores and ML models for sICH prediction

Tools	AUC Diff (XGBoost – Target)	p value
SEDAN	0.344	0
MSS	0.259	<0.001
HAT	0.142	0.014
GRASPS	0.180	0.006
SITS	0.199	0.002
SPAN-100	0.379	0
Logistic	0.024	0.579
RandomForest	0.024	0.403