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©The Author(s) 2021.
World J Gastrointest Oncol. Nov 15, 2021; 13(11): 1599-1615
Published online Nov 15, 2021. doi: 10.4251/wjgo.v13.i11.1599
Published online Nov 15, 2021. doi: 10.4251/wjgo.v13.i11.1599
Figure 1 General workflow of radiomics and deep learning in hepatocellular carcinoma.
Figure 2 Summary of the clinical application scenario, limitations, challenges, and further work of state-of-the-art radiomics and deep learning in hepatocellular carcinoma.
- Citation: Yao S, Ye Z, Wei Y, Jiang HY, Song B. Radiomics in hepatocellular carcinoma: A state-of-the-art review. World J Gastrointest Oncol 2021; 13(11): 1599-1615
- URL: https://www.wjgnet.com/1948-5204/full/v13/i11/1599.htm
- DOI: https://dx.doi.org/10.4251/wjgo.v13.i11.1599