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For: Kim DW, Lee G, Kim SY, Ahn G, Lee JG, Lee SS, Kim KW, Park SH, Lee YJ, Kim N. Deep learning-based algorithm to detect primary hepatic malignancy in multiphase CT of patients at high risk for HCC. Eur Radiol 2021;31:7047-57. [PMID: 33738600 DOI: 10.1007/s00330-021-07803-2] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
Number Citing Articles
1 Wei J, Jiang H, Zhou Y, Tian J, Furtado FS, Catalano OA. Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinoma. Dig Liver Dis 2023:S1590-8658(22)00863-5. [PMID: 36641292 DOI: 10.1016/j.dld.2022.12.015] [Reference Citation Analysis]
2 Fahmy D, Alksas A, Elnakib A, Mahmoud A, Kandil H, Khalil A, Ghazal M, van Bogaert E, Contractor S, El-Baz A. The Role of Radiomics and AI Technologies in the Segmentation, Detection, and Management of Hepatocellular Carcinoma. Cancers (Basel) 2022;14. [PMID: 36551606 DOI: 10.3390/cancers14246123] [Reference Citation Analysis]
3 Martinino A, Aloulou M, Chatterjee S, Scarano Pereira JP, Singhal S, Patel T, Kirchgesner TP, Agnes S, Annunziata S, Treglia G, Giovinazzo F. Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review. JCM 2022;11:6368. [DOI: 10.3390/jcm11216368] [Reference Citation Analysis]
4 Cheng C, Cai J, Teng W, Zheng Y, Huang Y, Wang Y, Peng C, Tang Y, Lee W, Yeh T, Xiao J, Lu L, Liao C, Harrison AP. A flexible three‐dimensional heterophase computed tomography hepatocellular carcinoma detection algorithm for generalizable and practical screening. Hepatology Communications. [DOI: 10.1002/hep4.2029] [Reference Citation Analysis]
5 Chen CI, Lu NH, Huang YH, Liu KY, Hsu SY, Matsushima A, Wang YM, Chen TB. Segmentation of liver tumors with abdominal computed tomography using fully convolutional networks. J Xray Sci Technol 2022. [PMID: 35754254 DOI: 10.3233/XST-221194] [Reference Citation Analysis]
6 Duc VT, Chien PC, Huyen LDM, Chau TLM, Chanh NDT, Soan DTM, Huyen HC, Thanh HM, Hy LNG, Nam NH, Uyen MTT, Nhi LHH, Minh LHN. Deep Learning Model With Convolutional Neural Network for Detecting and Segmenting Hepatocellular Carcinoma in CT: A Preliminary Study. Cureus 2022. [DOI: 10.7759/cureus.21347] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Peng J, Huang J, Huang G, Zhang J. Predicting the Initial Treatment Response to Transarterial Chemoembolization in Intermediate-Stage Hepatocellular Carcinoma by the Integration of Radiomics and Deep Learning. Front Oncol 2021;11:730282. [PMID: 34745952 DOI: 10.3389/fonc.2021.730282] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Kröner PT, Engels MM, Glicksberg BS, Johnson KW, Mzaik O, van Hooft JE, Wallace MB, El-Serag HB, Krittanawong C. Artificial intelligence in gastroenterology: A state-of-the-art review. World J Gastroenterol 2021; 27(40): 6794-6824 [PMID: 34790008 DOI: 10.3748/wjg.v27.i40.6794] [Cited by in CrossRef: 14] [Cited by in F6Publishing: 14] [Article Influence: 7.0] [Reference Citation Analysis]