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©The Author(s) 2024.
World J Radiol. Jun 28, 2024; 16(6): 203-210
Published online Jun 28, 2024. doi: 10.4329/wjr.v16.i6.203
Published online Jun 28, 2024. doi: 10.4329/wjr.v16.i6.203
Figure 2 Performance comparison of the gradient boosting tree models and the tumor node-staging system.
A: Performance assessment of the full model and reduced model. The full model included 23 selected variables. The reduced model only included the top-five variables. Area under the curve (AUC) is showed with 95% confidence interval (CI); B: Comparison of metastasis predictive performance among different predictive strategies in the whole dataset. Predictive strategies included using T-staging scores, N-stating scores, TN-staging scores, reduced model, and full model. The reduced model only included the top-five variables, while the full model included 23 selected variables. AUC is showed with 95%CI. AUC: Area under the curve.
- Citation: Zhu YL, Deng XL, Zhang XC, Tian L, Cui CY, Lei F, Xu GQ, Li HJ, Liu LZ, Ma HL. Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports. World J Radiol 2024; 16(6): 203-210
- URL: https://www.wjgnet.com/1949-8470/full/v16/i6/203.htm
- DOI: https://dx.doi.org/10.4329/wjr.v16.i6.203