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Table 3 Performances of machine learning models in prediction of the probability of and the time to the development of HCC

From: Prediction of the risk of developing hepatocellular carcinoma in health screening examinees: a Korean cohort study

Model Evaluation metric CV or OOB error in the training cohort Validation in the test cohort
Value (±SD) AUC (95% CI)
Probability of developing HCC within 10 years
 Random survival forest AUC 0.871 (±0.019)  
BSS 0.062  
 Extreme gradient boosting AUC 0.882 (±0.013)  
BSS 0.109  
 Ensemble of two models AUC 0.892 (±0.011) 0.873 (0.860–0.885)
BSS 0.112 0.078
Time to cancer occurrence if HCC develops
 Cox proportional hazard C-index 0.843 (±0.006) 0.828 (0.819–0.838)
 Random survival forest C-index 0.881 (±0.010) 0.857 (0.850–0.864)
  1. HCC hepatocellular carcinoma, CV cross validation, OOB out-of-bag, SD standard deviation, AUC area under receiver operating characteristics curve, CI confidence interval, BSS Brier skill score, C-index concordance index