Bayesian modeling of pretransplant variables accurately predicts kidney graft survival

Authors

Trevor S. Brown, Naval Medical Center, Bethesda, MD
Eric A. Elster, Uniformed Services University of the Health Sciences, Bethesda, MD
Kristin Stevens, Naval Medical Center, Bethesda, MD
J. Christopher Graybill, Naval Medical Center, Bethesda, MD
Suzanne Gillern, Naval Medical Center, Bethesda, MD
Samuel Phinney, Naval Medical Center, Bethesda, MD
Moro O. Salifu, SUNY Downstate Medical Center
Rahul M. Jindal, George Washington UniversityFollow

Document Type

Journal Article

Publication Date

2012

Journal

American Journal of Nephrology

Volume

Volume 36, Issue 6

Inclusive Pages

561-569

Keywords

Forecasting--methods; Graft Survival; Kidney Failure; Chronic--surgery; Kidney Transplantation

APA Citation

Brown, T.S., Elster, E.A., Stevens, K.,. Graybill, J.C., Gillern, S., Phinney, S., Salifu, M.O., Jindal, R.M. (2012). Bayesian modeling of pretransplant variables accurately predicts kidney graft survival. American Journal of Nephrology, 36(6), 561-569.

Peer Reviewed

1