Skip to Main content Skip to Navigation
Conference papers

Exploiting Machine Learning for Predicting Nodal Status in Prostate Cancer Patients

Abstract : Prostate cancer is the second cause of cancer in males. The prophylactic pelvic irradiation is usually needed for treating prostate cancer patients with Subclinical Nodal Metestases. Currently, the physicians decide when to deliver pelvic irradiation in nodal negative patients mainly by using the Roach formula, which gives an approximate estimation of the risk of Subclinical Nodal Metestases.In this paper we study the exploitation of Machine Learning techniques for training models, based on several pre-treatment parameters, that can be used for predicting the nodal status of prostate cancer patients. An experimental retrospective analysis, conducted on the largest Italian database of prostate cancer patients treated with radical External Beam Radiation Therapy, shows that the proposed approaches can effectively predict the nodal status of patients.
Document type :
Conference papers
Complete list of metadata

Cited literature [21 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Tuesday, February 7, 2017 - 1:07:33 PM
Last modification on : Monday, August 24, 2020 - 2:48:06 PM
Long-term archiving on: : Monday, May 8, 2017 - 2:13:20 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Mauro Vallati, Berardino De Bari, Roberto Gatta, Michela Buglione, Stefano M. Magrini, et al.. Exploiting Machine Learning for Predicting Nodal Status in Prostate Cancer Patients. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. pp.61-70, ⟨10.1007/978-3-642-41142-7_7⟩. ⟨hal-01459665⟩



Record views


Files downloads