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Cited by in F6Publishing
For: Yu HM, Wang K, Feng JK, Lu L, Qin YC, Cheng YQ, Guo WX, Shi J, Cong WM, Lau WY, Dong H, Cheng SQ. Image-matching digital macro-slide-a novel pathological examination method for microvascular invasion detection in hepatocellular carcinoma. Hepatol Int 2022. [PMID: 35294742 DOI: 10.1007/s12072-022-10307-w] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Yang X, Shao G, Liu J, Liu B, Cai C, Zeng D, Li H. Predictive machine learning model for microvascular invasion identification in hepatocellular carcinoma based on the LI-RADS system. Front Oncol 2022;12. [DOI: 10.3389/fonc.2022.1021570] [Reference Citation Analysis]
2 Wang K, Xiang Y, Yan J, Zhu Y, Chen H, Yu H, Cheng Y, Li X, Dong W, Ji Y, Li J, Xie D, Lau WY, Yao J, Cheng S. A deep learning model with incorporation of microvascular invasion area as a factor in predicting prognosis of hepatocellular carcinoma after R0 hepatectomy. Hepatol Int 2022. [PMID: 36001229 DOI: 10.1007/s12072-022-10393-w] [Reference Citation Analysis]