An innovative method to predict Nodal (N) status using an Artificial Intelligence approach in the low risk prostate cancer patients (pts): beyond the Roach formula?

De Bari, Berardino, Vallati, Mauro, Gatta, Roberto, Pasinetti, Nicola, Girelli, Giuseppe, Munoz, Fernando, Livi, Lorenzo, Bellavita, Rita, Krengli, Marco, Cagna, Emanuela, Bunkheila, Feisal, Signor, Marco and Magrini, Stefano (2012) An innovative method to predict Nodal (N) status using an Artificial Intelligence approach in the low risk prostate cancer patients (pts): beyond the Roach formula? In: 22nd Congress of the Italian Association for Radiation Oncology (AIRO), 17th - 20th November 2012, Rome, Italy. (Submitted)

[+][-]

Abstract

To present an innovative approach based on the methods of Artificial Intelligence to better predict N status in low risk prostate cancer pts, integrating some important clinical and herapeutic parameters (Gleason Score/sum, age, initial PSA, neoadjuvant or neoadjuvant/concomitant hormonal therapy vs no hormonal therapy), known before radiotherapy (RT).

Information

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI:

https://eprints.hud.ac.uk/id/eprint/15379

URI: