Literature DB >> 19034001

For an always promising transplant prediction, call ANN.

David W Gjertson1, Bill D Clark.   

Abstract

With apologies to Sherlock Holmes, "You can never foretell when any one man's kidney transplant will fail, but you can say with precision when an average number will fail. ... So says the statistician."

Entities:  

Mesh：

Year:  2008        PMID： 19034001      PMCID： PMC2605941          DOI： 10.1097/TP.0b013e31818b2417

Source DB:  PubMed          Journal:  Transplantation        ISSN： 0041-1337            Impact factor:   4.939


  5 in total

1.  On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology.

Authors:  G Schwarzer; W Vach; M Schumacher
Journal:  Stat Med       Date:  2000-02-29       Impact factor: 2.373

Review 2.  A review of evidence of health benefit from artificial neural networks in medical intervention.

Authors:  P J G Lisboa
Journal:  Neural Netw       Date:  2002-01

3.  Non-linear survival analysis using neural networks.

Authors:  Ruth M Ripley; Adrian L Harris; Lionel Tarassenko
Journal:  Stat Med       Date:  2004-03-15       Impact factor: 2.373

4.  Introduction to neural networks.

Authors:  S S Cross; R F Harrison; R L Kennedy
Journal:  Lancet       Date:  1995-10-21       Impact factor: 79.321

5.  Prediction of graft survival of living-donor kidney transplantation: nomograms or artificial neural networks?

Authors:  Ahmed Akl; Amani M Ismail; Mohamed Ghoneim
Journal:  Transplantation       Date:  2008-11-27       Impact factor: 4.939
  5 in total

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