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Cited by in CrossRef
For: Zhang YB, Yang G, Bu Y, Lei P, Zhang W, Zhang DY. Development of a machine learning-based model for predicting risk of early postoperative recurrence of hepatocellular carcinoma. World J Gastroenterol 2023; 29(43): 5804-5817 [PMID: 38074914 DOI: 10.3748/wjg.v29.i43.5804]
URL: https://www.wjgnet.com/1949-8470/full/v29/i43/5804.htm
Number Citing Articles
1
Mariana Michelle Ramírez-Mejía, Nahum Méndez-Sánchez. From prediction to prevention: Machine learning revolutionizes hepatocellular carcinoma recurrence monitoringWorld Journal of Gastroenterology 2024; 30(7): 631-635 doi: 10.3748/wjg.v30.i7.631
2
Ghada Mostafa, Hamdi Mahmoud, Tarek Abd El-Hafeez, Mohamed E. ElAraby. Feature reduction for hepatocellular carcinoma prediction using machine learning algorithmsJournal of Big Data 2024; 11(1) doi: 10.1186/s40537-024-00944-3
3
Giovanna McGinty, Robert Przemioslo. Effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease: Clinical implicationsWorld Journal of Gastroenterology 2024; 30(27): 3264-3267 doi: 10.3748/wjg.v30.i27.3264
4
Jing-Feng Chen, Zhuo-Qing Wu, Hao-Shuang Liu, Su Yan, You-Xiang Wang, Miao Xing, Xiao-Qin Song, Su-Ying Ding. Cumulative effects of excess high-normal alanine aminotransferase levels in relation to new-onset metabolic dysfunction-associated fatty liver disease in ChinaWorld Journal of Gastroenterology 2024; 30(10): 1346-1357 doi: 10.3748/wjg.v30.i10.1346
5
Mingqi Zhang, Bingling Kuang, Jingxuan Zhang, Jingyi Peng, Haoming Xia, Xiaobin Feng, Liang Peng. Enhancing prognostic prediction in hepatocellular carcinoma post-TACE: a machine learning approach integrating radiomics and clinical featuresFrontiers in Medicine 2024; 11 doi: 10.3389/fmed.2024.1419058