Prostate cancer nomograms are superior to neural networks
Karakiewicz I. Pierre; Chun K.-H. Felix; Briganti Alberto; Perrotte Paul; McCormack Michael; Benard Francois; Valiquette Luc; Graefen Markus; Saad Fred;
Department of Urology, University of Montreal, Montreal, Quebec, Canada
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.