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©The Author(s) 2025.
World J Gastroenterol. Jan 21, 2025; 31(3): 102283
Published online Jan 21, 2025. doi: 10.3748/wjg.v31.i3.102283
Published online Jan 21, 2025. doi: 10.3748/wjg.v31.i3.102283
Figure 4 Receiver operating characteristic curves of the radiomic signature based on different machine learning models.
A: Receiver operating characteristic (ROC) curves in the training cohort; B: ROC curves in the test cohort. AUC: Area under the receiver operating characteristic curve; LR; Logistic regression; SVM: Support vector machine; ExtraTrees: Extremely randomized trees; XGBoost: Extreme gradient boosting; LightGBM: Light gradient boosting machine; 95%CI: 95% confidence interval.
- Citation: Ding H, Fang YY, Fan WJ, Zhang CY, Wang SF, Hu J, Han W, Mei Q. Computed tomography enterography-based radiomics for assessing mucosal healing in patients with small bowel Crohn's disease. World J Gastroenterol 2025; 31(3): 102283
- URL: https://www.wjgnet.com/1007-9327/full/v31/i3/102283.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i3.102283