Copyright: ©Author(s) 2026.
Figure 9 Decision curve analysis for the training and testing cohorts.
A: Decision curve of the model in the training cohort, showing the net clinical benefit across a range of threshold probabilities; B: Decision curve of the model in the testing cohort, presenting the model’s clinical utility when applied to unseen data. Clinic: Clinical model; ALL: Random forest radiomics model; Nomogram: Combined model; DCA: Decision curve analysis.
- Citation: Zheng ZH, Wu CH, Hu JB, Xu JF, Zi XY, Chen JH, He Q, Dong WY. Computed tomography radiomics-based machine learning nomogram for preoperative prediction of glypican-3 expression in hepatocellular carcinoma. World J Radiol 2026; 18(7): 121161
- URL: https://www.wjgnet.com/1949-8470/full/v18/i7/121161.htm
- DOI: https://dx.doi.org/10.4329/wjr.121161