Table 6.

Performance evaluation of the selected ML algorithms for COVID-19 death prediction

Algorithms	Sensitivity (%)	Specificity (%)	Accuracy (%)	Precision (%)	ROC (%)
Random forest	90.70	95.10	95.03	94.23	99.02
XGBoost	90.89	95.01	94.25	92.43	98.18
KNN	97.38	82.15	89.56	80.11	96.78
MLP	90.81	91.07	91.25	87.19	96.49
Logistic regression	91.45	84.47	91.23	83.94	94.22
J48 decision tree	87.77	94.47	92.17	89.97	92.19
Naïve Bayes	90.44	84.31	87.47	81.32	92.05