XGBoost Outperforms Traditional Transplant Regulatory Models Based on Regression
- DOI
- 10.1097/as9.0000000000000698
- Published
- 2026-08-05
- Container
- Annals of Surgery Open
- Publisher
- Ovid Technologies (Wolters Kluwer Health)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1097/as9.0000000000000698,
title = {XGBoost Outperforms Traditional Transplant Regulatory Models Based on Regression},
author = {Rowland W. Pettit and Nicholas J. Cione and Britton B. Marlatt and Selim Uzgoren and Anil P. Shetty and Gwendolyn Henry and Jim Havelka and John A. Goss and Abbas A. Rana},
year = {2026},
journal = {Annals of Surgery Open},
doi = {10.1097/as9.0000000000000698},
url = {https://doi.org/10.1097/as9.0000000000000698}
}RIS
TY - JOUR TI - XGBoost Outperforms Traditional Transplant Regulatory Models Based on Regression AU - Rowland W. Pettit AU - Nicholas J. Cione AU - Britton B. Marlatt AU - Selim Uzgoren AU - Anil P. Shetty AU - Gwendolyn Henry AU - Jim Havelka AU - John A. Goss AU - Abbas A. Rana PY - 2026 JO - Annals of Surgery Open DO - 10.1097/as9.0000000000000698 UR - https://doi.org/10.1097/as9.0000000000000698 ER -
APA
Pettit, R. W., Cione, N. J., Marlatt, B. B., Uzgoren, S., Shetty, A. P., Henry, G., Havelka, J., Goss, J. A., & Rana, A. A. (2026). XGBoost Outperforms Traditional Transplant Regulatory Models Based on Regression. Annals of Surgery Open. https://doi.org/10.1097/as9.0000000000000698
Source records
- crossref · retrieved 2026-11-10T19:08:26.087Z