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Cited by in F6Publishing
For: Yang Y, Zhou Y, Zhou C, Ma X. Deep learning radiomics based on contrast enhanced computed tomography predicts microvascular invasion and survival outcome in early stage hepatocellular carcinoma. Eur J Surg Oncol 2021:S0748-7983(21)00927-6. [PMID: 34862094 DOI: 10.1016/j.ejso.2021.11.120] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Wang L, Wu M, Li R, Xu X, Zhu C, Feng X. MVI-Mind: A Novel Deep-Learning Strategy Using Computed Tomography (CT)-Based Radiomics for End-to-End High Efficiency Prediction of Microvascular Invasion in Hepatocellular Carcinoma. Cancers (Basel) 2022;14:2956. [PMID: 35740620 DOI: 10.3390/cancers14122956] [Reference Citation Analysis]