Computed tomography radiomics-based machine learning nomogram for preoperative prediction of glypican-3 expression in hepatocellular carcinoma

doi:10.4329/wjr.121161

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World Journal of Radiology

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1949-8470

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Radiol. Jul 28, 2026; 18(7): 121161
Published online Jul 28, 2026. doi: 10.4329/wjr.121161

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Figure 2 Computed tomography radiomics features and their corresponding correlation coefficients.

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

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 [PMID: 42534435 DOI: 10.4329/wjr.121161]

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