Transplantation: Neural networks for predicting graft survival

Bruce Kaplan; Jesse Schold

doi:10.1038/nrneph.2009.24

Transplantation: Neural networks for predicting graft survival

Bruce Kaplan, Jesse Schold

Research output: Contribution to journal › Short survey › peer-review

17 Scopus citations

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 language	English (US)
Pages (from-to)	190-192
Number of pages	3
Journal	Nature Reviews Nephrology
Volume	5
Issue number	4
DOIs	https://doi.org/10.1038/nrneph.2009.24
State	Published - Apr 2009
Externally published	Yes

ASJC Scopus subject areas

Nephrology

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10.1038/nrneph.2009.24

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title = "Transplantation: Neural networks for predicting graft survival",

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.",

author = "Bruce Kaplan and Jesse Schold",

year = "2009",

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volume = "5",

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T2 - Neural networks for predicting graft survival

AU - Kaplan, Bruce

AU - Schold, Jesse

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Transplantation: Neural networks for predicting graft survival

Abstract

ASJC Scopus subject areas

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