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Cited by in F6Publishing
For: Su TH, Wu CH, Kao JH. Artificial intelligence in precision medicine in hepatology. J Gastroenterol Hepatol 2021;36:569-80. [PMID: 33709606 DOI: 10.1111/jgh.15415] [Cited by in Crossref: 3] [Cited by in F6Publishing: 11] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Oh SH, Lee SJ, Park J. Effective data-driven precision medicine by cluster-applied deep reinforcement learning. Knowledge-Based Systems 2022;256:109877. [DOI: 10.1016/j.knosys.2022.109877] [Reference Citation Analysis]
2 Guo Q, Zhang J, Guo S, Ye Z, Deng H, Hou X, Zhang H. Urban Tree Classification Based on Object-Oriented Approach and Random Forest Algorithm Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery. Remote Sensing 2022;14:3885. [DOI: 10.3390/rs14163885] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
3 Lonardo A. Precision medicine in nonalcoholic fatty liver disease. J Gastroenterol Hepatol 2022;37:1175-8. [PMID: 35801994 DOI: 10.1111/jgh.15850] [Reference Citation Analysis]
4 Carteri RB, Grellert M, Borba DL, Marroni CA, Fernandes SA. Machine learning approaches using blood biomarkers in non-alcoholic fatty liver diseases. Artif Intell Gastroenterol 2022; 3(3): 80-87 [DOI: 10.35712/aig.v3.i3.80] [Reference Citation Analysis]
5 Iadanza E, Benincasa G, Ventisette I, Gherardelli M. Automatic Classification of Hospital Settings through Artificial Intelligence. Electronics 2022;11:1697. [DOI: 10.3390/electronics11111697] [Reference Citation Analysis]
6 Perisetti A, Goyal H, Yendala R, Chandan S, Tharian B, Thandassery RB. Sarcopenia in hepatocellular carcinoma: Current knowledge and future directions. World J Gastroenterol 2022; 28(4): 432-448 [DOI: 10.3748/wjg.v28.i4.432] [Cited by in CrossRef: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Yang Y, Siau K, Xie W, Sun Y. Smart Health: Intelligent Healthcare Systems in the Metaverse, Artificial Intelligence, and Data Science Era. Journal of Organizational and End User Computing 2022;34:1-14. [DOI: 10.4018/joeuc.308814] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
8 Zhuang H, Zhang J, Liao F. A systematic review on application of deep learning in digestive system image processing. Vis Comput 2021;:1-16. [PMID: 34744231 DOI: 10.1007/s00371-021-02322-z] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
9 Su TH, Hsu SJ, Kao JH. Paradigm shift in the treatment options of hepatocellular carcinoma. Liver Int 2021. [PMID: 34515412 DOI: 10.1111/liv.15052] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
10 Su TH, Hsu SJ, Kao JH. Systemic therapy for hepatocellular carcinoma: New agents and therapeutic hierarchy. J Formos Med Assoc 2021:S0929-6646(21)00394-6. [PMID: 34454796 DOI: 10.1016/j.jfma.2021.08.018] [Reference Citation Analysis]
11 Li Y, Wang X, Zhang J, Zhang S, Jiao J. Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD) : A systematic review. Rev Endocr Metab Disord 2021. [PMID: 34396467 DOI: 10.1007/s11154-021-09681-x] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Zhang C, Yang M. The Emerging Factors and Treatment Options for NAFLD-Related Hepatocellular Carcinoma. Cancers (Basel) 2021;13:3740. [PMID: 34359642 DOI: 10.3390/cancers13153740] [Cited by in F6Publishing: 12] [Reference Citation Analysis]