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Cited by in F6Publishing
For: Kim HY, Lampertico P, Nam JY, Lee HC, Kim SU, Sinn DH, Seo YS, Lee HA, Park SY, Lim YS, Jang ES, Yoon EL, Kim HS, Kim SE, Ahn SB, Shim JJ, Jeong SW, Jung YJ, Sohn JH, Cho YK, Jun DW, Dalekos GN, Idilman R, Sypsa V, Berg T, Buti M, Calleja JL, Goulis J, Manolakopoulos S, Janssen H, Jang MJ, Lee YB, Kim YJ, Yoon JH, Papatheodoridis GV, Lee JH. An artificial intelligence model to predict hepatocellular carcinoma risk in Korean and Caucasian patients with chronic hepatitis B. J Hepatol 2021:S0168-8278(21)02087-0. [PMID: 34606915 DOI: 10.1016/j.jhep.2021.09.025] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Wang Y, Wei C, Deng X, Gao S, Chen J, Mishra SK. Preliminary Evaluation of Artificial Intelligence-Based Anti-Hepatocellular Carcinoma Molecular Target Study in Hepatocellular Carcinoma Diagnosis Research. BioMed Research International 2022;2022:1-11. [DOI: 10.1155/2022/8365565] [Reference Citation Analysis]
2 Wang H, Ou Y, Fan T, Zhao J, Kang M, Dong R, Qu Y. Development and Internal Validation of a Nomogram to Predict Mortality During the ICU Stay of Thoracic Fracture Patients Without Neurological Compromise: An Analysis of the MIMIC-III Clinical Database. Front Public Health 2021;9:818439. [PMID: 35004604 DOI: 10.3389/fpubh.2021.818439] [Reference Citation Analysis]