Abstract

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• 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.