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©The Author(s) 2024.
World J Gastrointest Oncol. Oct 15, 2024; 16(10): 4115-4128
Published online Oct 15, 2024. doi: 10.4251/wjgo.v16.i10.4115
Published online Oct 15, 2024. doi: 10.4251/wjgo.v16.i10.4115
Figure 4 Receiver operating characteristic curve analysis of the radiomic model and the clinical model.
A: The area under the curve (AUC) of the radiomic model was 1.000 [95% confidence interval (CI): 1.000-1.000] in the training cohort; B: The AUC of the radiomic model was 0.750 (95%CI: 0.435-1.000) in the test cohort; C: The AUC of the clinical model was 0.937 (95%CI: 0.868-1.000) in the training cohort; D: The AUC of the clinical model was 0.696 (95%CI: 0.440-0.953) in the test cohort. XGBoost: EXtreme gradient boosting; TPR: True positive rate; FPR: False positive rate.
- Citation: Zhang J, Wang Q, Guo TH, Gao W, Yu YM, Wang RF, Yu HL, Chen JJ, Sun LL, Zhang BY, Wang HJ. Computed tomography-based radiomic model for the prediction of neoadjuvant immunochemotherapy response in patients with advanced gastric cancer. World J Gastrointest Oncol 2024; 16(10): 4115-4128
- URL: https://www.wjgnet.com/1948-5204/full/v16/i10/4115.htm
- DOI: https://dx.doi.org/10.4251/wjgo.v16.i10.4115