BAYESIAN MODELING OF THE UNITED STATES RENAL DATA SYSTEM PRE-TRANSPLANT VARIABLES ACCURATELY PREDICTS GRAFT SURVIVAL: 278

Research output: Contribution to journal › Article › peer-review

Cite this

@article{568cc0b456bd41cea5e55f1df9cc93fd,

title = "BAYESIAN MODELING OF THE UNITED STATES RENAL DATA SYSTEM PRE-TRANSPLANT VARIABLES ACCURATELY PREDICTS GRAFT SURVIVAL: 278",

author = "KA Stevens and S Phinney and C Graybill and S Gillern and M Salifu and R Jindal and T Brown and E Elster",

year = "2010",

language = "Undefined/Unknown",

volume = "90",

pages = "285",

journal = "Transplantation",

issn = "0041-1337",

publisher = "Lippincott Williams and Wilkins",

}

TY - JOUR

T1 - BAYESIAN MODELING OF THE UNITED STATES RENAL DATA SYSTEM PRE-TRANSPLANT VARIABLES ACCURATELY PREDICTS GRAFT SURVIVAL: 278

AU - Stevens, KA

AU - Phinney, S

AU - Graybill, C

AU - Gillern, S

AU - Salifu, M

AU - Jindal, R

AU - Brown, T

AU - Elster, E

PY - 2010

Y1 - 2010

M3 - Article

SN - 0041-1337

VL - 90

SP - 285

JO - Transplantation

JF - Transplantation

ER -