©The Author(s) 2025.
World J Gastroenterol. Nov 14, 2025; 31(42): 112180
Published online Nov 14, 2025. doi: 10.3748/wjg.v31.i42.112180
Published online Nov 14, 2025. doi: 10.3748/wjg.v31.i42.112180
Figure 12 Receiver operating characteristic, precision-recall curve, calibration curves and decision curve analysis for the optimal prediction model clinic-machine learning nomogram (testing set).
A: Receiver operating characteristic curve; B: Precision-recall curve; C: Calibration curve; D: Decision curve analysis. AUC: Area under the curve; ML: Machine learning; AUPRC: Area under the precision-recall curve; CI: Confidence interval.
- Citation: Liu YM, Du YY, Song Y, Xiong HT, Yu HB, Li BH, Cai L, Ma SS, Gao J, Zhang HY, Fang RY, Cai R, Zheng HG. Predicting chemotherapy-induced myelosuppression in colorectal cancer: An interpretable, machine learning-based nomogram. World J Gastroenterol 2025; 31(42): 112180
- URL: https://www.wjgnet.com/1007-9327/full/v31/i42/112180.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i42.112180