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)

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).

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