Pain management in patients with hepatocellular carcinoma after transcatheter arterial chemoembolisation: A retrospective study

Table 2 The receiver operating characteristic curve analyses for pain risk in each machine learning-based model

Model	Training set		Testing set
	AUC mean	AUC 95%CI	AUC mean	AUC 95%CI
RFM	0.869	0.816-0.922	0.871	0.818-0.924
DTM	0.861	0.808-0.914	0.864	0.811-0.917
ANNM	0.826	0.773-0.879	0.827	0.774-0.880
SVMM	0.803	0.750-0.856	0.808	0.755-0.861
NBM	0.798	0.745-0.851	0.803	0.750-0.856

RFM: Random forest model; SVMM: Support vector machine model; DTM: Decision tree model; ANNM: Artificial neural network model; NBM: Naive Bayesian model; AUC: Area under curve; 95%CI: 95% confidence interval.