Tools
Tools
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)
![[img]](http://eprints.hud.ac.uk/style/images/fileicons/application_msword.png) | Microsoft Word - Supplemental Material Download (32kB) |
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).
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > R Medicine (General) |
| Schools: | School of Computing and Engineering School of Computing and Engineering > Informatics Research Group > Knowledge Engineering and Intelligent Interfaces |
| Depositing User: | Mauro Vallati |
| Date Deposited: | 25 Oct 2012 12:19 |
| Last Modified: | 25 Oct 2012 12:19 |
| URI: | http://eprints.hud.ac.uk/id/eprint/15379 |
Item control for Repository Staff only:
| View Item |