Table 2.

Performance of All ML Models for HCC Prediction

Metric	Value by algorithm
	GB	NB	PNN	DT	RF
Accuracy	92.12	68.08	81.92	87.17	90.29
AUC	0.97	0.64	0.91	0.87	0.97
Specificity	98.24	36.41	100.00	76.47	96.60
Sensitivity	74.42	79.01	29.54	84.31	74.23
NPV	91.76	83.41	80.28	93.38	91.57
PPV	93.92	30.01	91.06	55.27	88.27
Cohen’s kappa	0.78	0.15	0.38	0.64	0.51
F1-score	0.84	0.37	0.46	0.73	0.84

DT, decision tree; GB, gradient boosted; NB, naïve bayes; NPV, negative predictive value; PNN, probabilistic neural network; PPV, positive predictive value; RF, random forest.