Copyright
©The Author(s) 2020.
World J Gastroenterol. Jul 7, 2020; 26(25): 3660-3672
Published online Jul 7, 2020. doi: 10.3748/wjg.v26.i25.3660
Published online Jul 7, 2020. doi: 10.3748/wjg.v26.i25.3660
Figure 4 The receiver operating characteristic analysis of model's classification performance on test set and calibration curve of model's classification probability for each category.
A: The receiver operating characteristic analysis of model's classification performance on test set; B: Calibration curve of model's classification probability for each category. FLLs: Focal liver lesions; HCC: Hepatocellular carcinoma; ROC: Receiver operating characteristic.
- Citation: Cao SE, Zhang LQ, Kuang SC, Shi WQ, Hu B, Xie SD, Chen YN, Liu H, Chen SM, Jiang T, Ye M, Zhang HX, Wang J. Multiphase convolutional dense network for the classification of focal liver lesions on dynamic contrast-enhanced computed tomography. World J Gastroenterol 2020; 26(25): 3660-3672
- URL: https://www.wjgnet.com/1007-9327/full/v26/i25/3660.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i25.3660