[Retracted] Establishment and Evaluation of Artificial Intelligence-Based Prediction Models for Chronic Kidney Disease under the Background of Big Data

Table 4

Prediction performance of the different models.

Model	Indicator				Indication with MD-BERT-LGBM
	Accuracy	Precision	Recall	AUC	Accuracy	Precision	Recall	AUC
XGBoost	0.9088	0.9175	0.8244	0.9549	0.9357	0.9425	0.8782	0.9719
SVM	0.8048	0.8330	0.5828	0.8705	0.7992	0.8392	0.5575	0.8704
NB	0.7811	0.8326	0.4973	0.8460	0.8086	0.8670	0.5556	0.7693
RF	0.9020	0.9318	0.7905	0.9519	0.9108	0.9550	0.7927	0.9716
LR	0.8276	0.7868	0.7225	0.8903	0.8489	0.8187	0.7551	0.9045

SVM, support vector machine, RF, random forest, NB, Naïve Bayes, LR, logistic regression model.