Fig. 1

A Receiver operating characteristic curves and B precision–recall curves of machine learning models on the testing dataset. C XGBoost yielded the highest area under the ROC curve for prediction of end-stage renal disease followed by extra trees classifier and GBDT on the testing dataset. Abbreviations: ROC, receiver operating characteristic; PR, precision–recall; AUC, area under curve of receiver operating characteristic curve; A.precision, average precision; AUC PRC, area under curve of precision-recall curve; GBDT, gradient boosting decision tree; XGBoost, extreme gradient boosting; LGBM, light gradient boosting machine