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Cited by in F6Publishing
For: Huang Y, Chen H, Zeng Y, Liu Z, Ma H, Liu J. Development and Validation of a Machine Learning Prognostic Model for Hepatocellular Carcinoma Recurrence After Surgical Resection. Front Oncol 2020;10:593741. [PMID: 33598425 DOI: 10.3389/fonc.2020.593741] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Christou CD, Tsoulfas G. Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities. World J Gastrointest Oncol 2022; 14(4): 765-793 [DOI: 10.4251/wjgo.v14.i4.765] [Reference Citation Analysis]
2 Zhang Y, Liu Z, Li X, Liu L, Wang L, Han X, Li Z. Comprehensive Molecular Analyses of a Six-Gene Signature for Predicting Late Recurrence of Hepatocellular Carcinoma. Front Oncol 2021;11:732447. [PMID: 34568069 DOI: 10.3389/fonc.2021.732447] [Reference Citation Analysis]
3 Wei L, Huang Y, Chen Z, Lei H, Qin X, Cui L, Zhuo Y. Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study. Front Oncol 2021;11:763381. [PMID: 34722318 DOI: 10.3389/fonc.2021.763381] [Reference Citation Analysis]
4 Liu IT, Yen CS, Wang WL, Tsai HW, Chu CY, Chang MY, Hou YF, Yen CJ. Predict Early Recurrence of Resectable Hepatocellular Carcinoma Using Multi-Dimensional Artificial Intelligence Analysis of Liver Fibrosis. Cancers (Basel) 2021;13:5323. [PMID: 34771487 DOI: 10.3390/cancers13215323] [Reference Citation Analysis]
5 Blidisel A, Marcovici I, Coricovac D, Hut F, Dehelean CA, Cretu OM. Experimental Models of Hepatocellular Carcinoma-A Preclinical Perspective. Cancers (Basel) 2021;13:3651. [PMID: 34359553 DOI: 10.3390/cancers13153651] [Cited by in F6Publishing: 1] [Reference Citation Analysis]