Transplantation: Neural networks for predicting graft survival

Nature Reviews Nephrology

Volumn 5, Issue 4, 2009, Pages 190-192

  Kaplan, Bruce ^a   Schold, Jesse ^b  

^a UNIVERSITY OF ARIZONA COLLEGE OF MEDICINE   (United States)

^b UNIVERSITY OF FLORIDA COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

STEROID;

ARTIFICIAL NEURAL NETWORK; GRAFT RECIPIENT; GRAFT SURVIVAL; HUMAN; IMMUNE RESPONSE; IMMUNOSUPPRESSIVE TREATMENT; KIDNEY DONOR; KIDNEY GRAFT REJECTION; KIDNEY TRANSPLANTATION; LIVING DONOR; PRIORITY JOURNAL; SHORT SURVEY; TREATMENT OUTCOME; BIOLOGICAL MODEL; NOTE; PREDICTION AND FORECASTING;

GRAFT SURVIVAL; HUMANS; KIDNEY TRANSPLANTATION; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); PREDICTIVE VALUE OF TESTS; TREATMENT OUTCOME;

EID: 67049165542     PISSN: 17595061     EISSN: 1759507X     Source Type: Journal    
DOI: 10.1038/nrneph.2009.24     Document Type: Short Survey

References (7)

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7. Meier-Kriesche, H. U., Schold, J. D., Srinivas, T. R. & Kaplan, B. Lack of improvement in renal allograft Survival despite a marked decrease in acute rejection rates over the most recent era. Am. J. Transplant. 4, 378-383 (2004).