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©The Author(s) 2022.
World J Gastrointest Oncol. Dec 15, 2022; 14(12): 2380-2392
Published online Dec 15, 2022. doi: 10.4251/wjgo.v14.i12.2380
Published online Dec 15, 2022. doi: 10.4251/wjgo.v14.i12.2380
Figure 2 Kaplan-Meier curves of overall survival stratified by high and low risk for clinical, deep learning-based radiomics, and clinical + deep learning-based radiomics models.
A and B: Clinical training; C and D: Deep learning-based radiomics testing; E and F: Clinical + DLR. DLR: Deep learning-based radiomics.
- Citation: Huang Z, Shu Z, Zhu RH, Xin JY, Wu LL, Wang HZ, Chen J, Zhang ZW, Luo HC, Li KY. Deep learning-based radiomics based on contrast-enhanced ultrasound predicts early recurrence and survival outcome in hepatocellular carcinoma. World J Gastrointest Oncol 2022; 14(12): 2380-2392
- URL: https://www.wjgnet.com/1948-5204/full/v14/i12/2380.htm
- DOI: https://dx.doi.org/10.4251/wjgo.v14.i12.2380