Comparison of predictive models for staging prostate cancer

This work presents a comparison between different predictive models with the aim of making the diagnosis and staging of prostate cancer in an automatic way. Nowadays, the estimations of size, localization and extension (stage) of the disease are made using the knowledge of previous cases. This paper presents an easy tool that allows using this information to have a new software application to predict the staging of the disease and to store the data. Besides, the application improves the present visualization tools for the prostate cancer, as in 2D visualization as a 3D volume.