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Cited by in F6Publishing
For: Yasodhara A, Dong V, Azhie A, Goldenberg A, Bhat M. Identifying Modifiable Predictors of Long-Term Survival in Liver Transplant Recipients With Diabetes Mellitus Using Machine Learning. Liver Transpl 2021;27:536-47. [PMID: 33113221 DOI: 10.1002/lt.25930] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Tran J, Sharma D, Gotlieb N, Xu W, Bhat M. Application of machine learning in liver transplantation: a review. Hepatol Int 2022. [PMID: 35020154 DOI: 10.1007/s12072-021-10291-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
2 Balch JA, Delitto D, Tighe PJ, Zarrinpar A, Efron PA, Rashidi P, Upchurch GR Jr, Bihorac A, Loftus TJ. Machine Learning Applications in Solid Organ Transplantation and Related Complications. Front Immunol 2021;12:739728. [PMID: 34603324 DOI: 10.3389/fimmu.2021.739728] [Reference Citation Analysis]
3 Khan MQ, Watt KD. Scientific Relief: When Science and Technology Agree and Lead. Liver Transpl 2021;27:484-5. [PMID: 33522080 DOI: 10.1002/lt.25998] [Reference Citation Analysis]
4 Peloso A, Moeckli B, Delaune V, Oldani G, Andres A, Compagnon P. Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation. Transpl Int 2022;35:10640. [DOI: 10.3389/ti.2022.10640] [Reference Citation Analysis]
5 Azhie A, Sheth P, Hammad A, Woo M, Bhat M. Metabolic Complications in Liver Transplantation Recipients: How We Can Optimize Long-Term Survival. Liver Transpl 2021. [PMID: 34165872 DOI: 10.1002/lt.26219] [Reference Citation Analysis]