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Cited by in F6Publishing
For: Wang N, Yang J, Lyu J, Liu Q, He H, Liu J, Li L, Ren X, Li Z. A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma. BMC Cancer 2020;20:505. [PMID: 32487033 DOI: 10.1186/s12885-020-06971-6] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
Number Citing Articles
1 Yin M, Lin J, Liu L, Gao J, Xu W, Yu C, Qu S, Liu X, Qian L, Xu C, Zhu J. Development of a Deep Learning Model for Malignant Small Bowel Tumors Survival: A SEER-Based Study. Diagnostics 2022;12:1247. [DOI: 10.3390/diagnostics12051247] [Reference Citation Analysis]
2 Yang QY, Tang CT, Huang YF, Shao DT, Shu X. Development and validation of a nomogram for primary duodenal carcinoma: a multicenter, population-based study. Future Oncol 2022. [PMID: 35114801 DOI: 10.2217/fon-2021-0622] [Reference Citation Analysis]
3 Li X, Xu H, Yan L, Gao J, Zhu L. A Novel Clinical Nomogram for Predicting Cancer-Specific Survival in Adult Patients After Primary Surgery for Epithelial Ovarian Cancer: A Real-World Analysis Based on the Surveillance, Epidemiology, and End Results Database and External Validation in a Tertiary Center. Front Oncol 2021;11:670644. [PMID: 33959514 DOI: 10.3389/fonc.2021.670644] [Reference Citation Analysis]
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