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Cited by in F6Publishing
For: Ning P, Gao F, Hai J, Wu M, Chen J, Zhu S, Wang M, Shi D. Application of CT radiomics in prediction of early recurrence in hepatocellular carcinoma. Abdom Radiol (NY). 2020;45:64-72. [PMID: 31486869 DOI: 10.1007/s00261-019-02198-7] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 8.0] [Reference Citation Analysis]
Number Citing Articles
1 Mai RY, Zeng J, Meng WD, Lu HZ, Liang R, Lin Y, Wu GB, Li LQ, Ma L, Ye JZ, Bai T. Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion. BMC Cancer 2021;21:283. [PMID: 33726693 DOI: 10.1186/s12885-021-07969-4] [Reference Citation Analysis]
2 Tang Y, Yang CM, Su S, Wang WJ, Fan LP, Shu J. Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma. BMC Cancer 2021;21:1268. [PMID: 34819043 DOI: 10.1186/s12885-021-08947-6] [Reference Citation Analysis]
3 Harding-Theobald E, Louissaint J, Maraj B, Cuaresma E, Townsend W, Mendiratta-Lala M, Singal AG, Su GL, Lok AS, Parikh ND. Systematic review: radiomics for the diagnosis and prognosis of hepatocellular carcinoma. Aliment Pharmacol Ther 2021;54:890-901. [PMID: 34390014 DOI: 10.1111/apt.16563] [Reference Citation Analysis]
4 Tang S, Ou J, Wu YP, Li R, Chen TW, Zhang XM. Contrast-enhanced CT radiomics features to predict recurrence of locally advanced oesophageal squamous cell cancer within 2 years after trimodal therapy: A case-control study. Medicine (Baltimore) 2021;100:e26557. [PMID: 34232198 DOI: 10.1097/MD.0000000000026557] [Reference Citation Analysis]
5 Bell M, Turkbey EB, Escorcia FE. Radiomics, Radiogenomics, and Next-Generation Molecular Imaging to Augment Diagnosis of Hepatocellular Carcinoma. Cancer J. 2020;26:108-115. [PMID: 32205534 DOI: 10.1097/ppo.0000000000000435] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
6 Tu HB, Chen LH, Huang YJ, Feng SY, Lin JL, Zeng YY. Novel model combining contrast-enhanced ultrasound with serology predicts hepatocellular carcinoma recurrence after hepatectomy. World J Clin Cases 2021; 9(24): 7009-7021 [PMID: 34540956 DOI: 10.12998/wjcc.v9.i24.7009] [Reference Citation Analysis]
7 Tang S, Ou J, Liu J, Wu YP, Wu CQ, Chen TW, Zhang XM, Li R, Tang MJ, Yang LQ, Tan BG, Lu FL, Hu J. Application of contrast-enhanced CT radiomics in prediction of early recurrence of locally advanced oesophageal squamous cell carcinoma after trimodal therapy. Cancer Imaging 2021;21:38. [PMID: 34039403 DOI: 10.1186/s40644-021-00407-5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Zhu HB, Zheng ZY, Zhao H, Zhang J, Zhu H, Li YH, Dong ZY, Xiao LS, Kuang JJ, Zhang XL, Liu L. Radiomics-based nomogram using CT imaging for noninvasive preoperative prediction of early recurrence in patients with hepatocellular carcinoma.Diagn Interv Radiol. 2020;26:411-419. [PMID: 32490826 DOI: 10.5152/dir.2020.19623] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
9 Brancato V, Garbino N, Salvatore M, Cavaliere C. MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma. Diagnostics 2022;12:1085. [DOI: 10.3390/diagnostics12051085] [Reference Citation Analysis]