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Cited by in CrossRef
For: Ramoni D, Liberale L, Montecucco F. Inflammatory biomarkers as cost-effective predictive tools in metabolic dysfunction-associated fatty liver disease. World J Gastroenterol 2024; 30(47): 5086-5091 [PMID: 39713167 DOI: 10.3748/wjg.v30.i47.5086]
URL: https://www.wjgnet.com/1949-8462/full/v30/i47/5086.htm
Number Citing Articles
1
Gangfeng Zhu, Yipeng Song, Zenghong Lu, Qiang Yi, Rui Xu, Yi Xie, Shi Geng, Na Yang, Liangjian Zheng, Xiaofei Feng, Rui Zhu, Xiangcai Wang, Li Huang, Yi Xiang. Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristicsJournal of Translational Medicine 2025; 23(1) doi: 10.1186/s12967-025-06387-5
2
Bratati Bandyopadhyay, Souparna Sasmal, Ayantika Kanrar, Shreya Adhikary. Reactive Oxygen Species in Metabolic Inflammation2026; : 157 doi: 10.1007/978-3-032-11752-6_8
3
Marcin Kosmalski, Łukasz Mokros. Non-Alcoholic Fatty Liver Disease in Everyday Clinical Practice: From Diagnosis to TherapyLife 2025; 15(3): 363 doi: 10.3390/life15030363