Liver stiffness-platelet ratio index and machine learning models for the noninvasive diagnosis of significant fibrosis in chronic hepatitis B

Table 3 Performance of machine learning and deep learning models with 26 features and liver stiffness-platelet ratio index + 26 features on imbalanced dataset

Models	Area under the receiver operating characteristic curve	Youden	Positive predictive value (%)	Negative predictive value (%)	Accuracy (%)	True positives (n)	False positive (n)	True negative (n)	False negative (n)	Sensitivity (%)	Specificity (%)
Using 26 features
LogisticRegression	0.85	0.58	0.57	0.92	0.80	41.40	31.60	134.00	12.40	0.77	0.81
SVM	0.83	0.55	0.55	0.91	0.79	40.40	33.40	132.20	13.40	0.75	0.80
NuSVC	0.81	0.52	0.51	0.91	0.76	41.40	40.80	124.80	12.40	0.77	0.75
DecisionTree	0.70	0.40	0.54	0.85	0.77	29.80	25.60	140.00	24.00	0.55	0.85
ExtraTree	0.63	0.27	0.44	0.82	0.72	24.80	32.00	133.60	29.00	0.46	0.81
GaussianNB	0.80	0.49	0.52	0.89	0.77	38.20	35.80	129.80	15.60	0.71	0.78
GradientBoosting	0.88	0.63	0.60	0.93	0.82	43.20	29.00	136.60	10.60	0.80	0.82
HistGradientBoosting	0.87	0.62	0.55	0.94	0.79	45.20	37.00	128.60	8.60	0.84	0.78
AdaBoost	0.86	0.61	0.54	0.95	0.78	46.20	41.60	124.00	7.60	0.86	0.75
RandomForest	0.87	0.62	0.58	0.93	0.81	44.00	32.00	133.60	9.80	0.82	0.81
KNeighbors	0.77	0.43	0.47	0.89	0.72	38.00	46.40	119.20	15.80	0.71	0.72
KAN	0.83	0.55	0.56	0.91	0.79	40.80	34.20	131.40	13.00	0.76	0.79
NeuralNetwork	0.84	0.57	0.55	0.92	0.78	42.80	36.80	128.80	11.00	0.80	0.78
Using liver stiffness-platelet ratio index + 26 features
LogisticRegression	0.85	0.58	0.58	0.91	0.81	40.80	29.00	136.60	13.00	0.76	0.82
SVM	0.83	0.55	0.54	0.91	0.78	41.00	34.80	130.80	12.80	0.76	0.79
NuSVC	0.81	0.53	0.54	0.91	0.77	40.40	37.20	128.40	13.40	0.75	0.78
DecisionTree	0.67	0.35	0.51	0.84	0.76	26.80	25.00	140.60	27.00	0.50	0.85
ExtraTree	0.66	0.32	0.48	0.83	0.75	26.40	28.40	137.20	27.40	0.49	0.83
GaussianNB	0.81	0.52	0.58	0.89	0.80	37.20	27.80	137.80	16.60	0.69	0.83
GradientBoosting	0.87	0.62	0.56	0.94	0.80	44.80	34.80	130.80	9.00	0.83	0.79
HistGradientBoosting	0.87	0.61	0.53	0.94	0.78	46.00	41.40	124.20	7.80	0.86	0.75
AdaBoost	0.85	0.58	0.59	0.92	0.80	42.00	33.00	132.60	11.80	0.78	0.80
RandomForest	0.86	0.64	0.62	0.93	0.82	43.60	28.80	136.80	10.20	0.81	0.83
KNeighbors	0.78	0.42	0.47	0.88	0.72	37.00	44.20	121.40	16.80	0.69	0.73
KAN	0.84	0.58	0.55	0.92	0.79	42.60	35.80	129.80	11.20	0.79	0.78
NeuralNetwork	0.85	0.59	0.59	0.92	0.81	41.00	28.80	136.80	12.80	0.76	0.83

SVM: Support vector machine; NuSVC: Nu-support vector classification; KAN: Kolmogorov-Arnold Network.