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Cited by in F6Publishing
For: Han T, Cheng T, Liao Y, He Y, Liu B, Lai Q, Pan P, Liu J, Lei C, Cao Y. Development and Validation of a Novel Prognostic Score Based on Thrombotic and Inflammatory Biomarkers for Predicting 28-Day Adverse Outcomes in Patients with Acute Pancreatitis. JIR 2022;Volume 15:395-408. [DOI: 10.2147/jir.s344446] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Yin M, Zhang R, Zhou Z, Liu L, Gao J, Xu W, Yu C, Lin J, Liu X, Xu C, Zhu J. Automated Machine Learning for the Early Prediction of the Severity of Acute Pancreatitis in Hospitals. Front Cell Infect Microbiol 2022;12:886935. [PMID: 35755847 DOI: 10.3389/fcimb.2022.886935] [Reference Citation Analysis]
2 Han T, Cheng T, Liao Y, Lai Q, Tang S, Liu B, He Y, Lei C, Cao Y, Cao Y. Thrombo-Inflammatory Prognostic Scores Improve BISAP-Based Risk Stratification in Acute Pancreatitis Patients: A Retrospective Cohort Study. JIR 2022;Volume 15:3323-35. [DOI: 10.2147/jir.s366246] [Reference Citation Analysis]
3 Liu Z, Yang Y, Song H, Luo J. A prediction model with measured sentiment scores for the risk of in-hospital mortality in acute pancreatitis: a retrospective cohort study. Ann Transl Med 2022;10:676. [PMID: 35845515 DOI: 10.21037/atm-22-1613] [Reference Citation Analysis]