Copyright
©The Author(s) 2024.
World J Gastrointest Surg. Mar 27, 2024; 16(3): 717-730
Published online Mar 27, 2024. doi: 10.4240/wjgs.v16.i3.717
Published online Mar 27, 2024. doi: 10.4240/wjgs.v16.i3.717
Figure 3 Performance of random forest model.
A: The receiver operating characteristic curves (ROC) of the random forest (RF) model in the training cohort; B: The ROC of the RF model in the validation cohort. AUC: Area under the curve.
- Citation: Wang FT, Lin Y, Yuan XQ, Gao RY, Wu XC, Xu WW, Wu TQ, Xia K, Jiao YR, Yin L, Chen CQ. Predicting short-term major postoperative complications in intestinal resection for Crohn’s disease: A machine learning-based study. World J Gastrointest Surg 2024; 16(3): 717-730
- URL: https://www.wjgnet.com/1948-9366/full/v16/i3/717.htm
- DOI: https://dx.doi.org/10.4240/wjgs.v16.i3.717