Prostate cancer nomograms are superior to neural networks.

Pierre I. Karakiewicz, Felix K H Chun, Alberto Briganti, Paul Perrotte, Michael McCormack, François Bénard, Luc Valiquette, Markus Graefen, Fred Saad

Research output: Contribution to journalArticlepeer-review

Abstract

INTRODUCTION: Several nomograms have been developed to predict PCa related outcomes. Neural networks represent an alternative. METHODS: We provide a descriptive and an analytic comparison of nomograms and neural networks, with focus on PCa detection. RESULTS: Our results indicate that nomograms have several advantages that distinguish them from neural networks. These are both quantitative and qualitative. CONCLUSION: In the field of PCa detection, nomograms appear to outweigh the benefits of neural networks. However, the neural network methodology represents a valid alternative, which should not be underestimated.

Original languageEnglish
Pages (from-to)18-25
Number of pages8
JournalThe Canadian journal of urology
Volume13 Suppl 2
Publication statusPublished - Apr 2006

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