| For: | Zuo XY, Liu HF. Biparametric magnetic resonance imaging-based radiomic and deep learning models for predicting Ki-67 risk stratification in hepatocellular carcinoma. World J Hepatol 2025; 17(8): 109530 [PMID: 40901605 DOI: 10.4254/wjh.v17.i8.109530] |
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| URL: | https://www.wjgnet.com/1948-5182/full/v17/i8/109530.htm |
| Number | Citing Articles |
| 1 |
Haibo Huang, Jie Yang, Yingdan Zhang, Xianpan Pan, Lei Chen, Yingying Huang, Xiaocheng Wang, Wei Lu, Zehe Huang, Ke Ding. Predictive Efficacy of a Combined Triphasic CT Radiomics and Clinical Feature Model for Ki-67 Expression in Hepatocellular Carcinoma. Journal of Hepatocellular Carcinoma 2026; doi: 10.2147/JHC.S605592
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| 2 |
Qing-Hua Ke, Shi-Qiong Zhou. Advancing precision in hepatocellular carcinoma prognostication: The promise of biparametric magnetic resonance imaging-based multimodal models. World Journal of Hepatology 2025; 17(10): 112078 doi: 10.4254/wjh.v17.i10.112078
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