Transplantation: Neural networks for predicting graft survival

Bruce Kaplan, Jesse Schold

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Predicting outcomes of renal transplant recipients using standard statistical techniques is difficult. novel approaches such as the use of artificial neural networks might improve the precision and accuracy in this area of medicine in which numerous and complex events contribute to outcomes.

Original languageEnglish (US)
Pages (from-to)190-192
Number of pages3
JournalNature Reviews Nephrology
Volume5
Issue number4
DOIs
StatePublished - Apr 2009
Externally publishedYes

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Graft Survival
Transplantation
Medicine
Kidney
Transplant Recipients

ASJC Scopus subject areas

  • Nephrology
  • Medicine(all)

Cite this

Transplantation : Neural networks for predicting graft survival. / Kaplan, Bruce; Schold, Jesse.

In: Nature Reviews Nephrology, Vol. 5, No. 4, 04.2009, p. 190-192.

Research output: Contribution to journalArticle

Kaplan, Bruce ; Schold, Jesse. / Transplantation : Neural networks for predicting graft survival. In: Nature Reviews Nephrology. 2009 ; Vol. 5, No. 4. pp. 190-192.
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