Table 5.

The logistic regression analysis to construct the stacking ML based Nomogram.

Outcome	Coef.	Bootstrap Std. Err.	Z	P>|z|	[95% conf. Interval]
Gradient Boosting (M1)	6.685314	0.7587142	8.81	0.000	5.198262	8.172367
Random Forest (M2)	1.3158	0.4752868	2.77	0.006	0.3842555	−2.247345
XGBoost (M3)	0.6338573	0.4685463	1.35	0.176	−0.2844766	−1.552191
cons	−3.516128	0.205643	−17.10	0.000	−3.919181	−3.113076