PO-0851: Artificial neural networks for toxicity prediction in RT: a method to validate their "intelligence". (May 2017)
- Record Type:
- Journal Article
- Title:
- PO-0851: Artificial neural networks for toxicity prediction in RT: a method to validate their "intelligence". (May 2017)
- Main Title:
- PO-0851: Artificial neural networks for toxicity prediction in RT: a method to validate their "intelligence"
- Authors:
- Massari, E.
Rancati, T.
Giandini, T.
Cicchetti, A.
Vavassori, V.
Fellin, G.
Avuzzi, B.
Cozzarini, C.
Fiorino, C.
Valdagni, R.
Carrara, M. - Abstract:
- Is Part Of:
- Radiotherapy and oncology. Volume 123:(2017:May)Supplement 1
- Journal:
- Radiotherapy and oncology
- Issue:
- Volume 123:(2017:May)Supplement 1
- Issue Display:
- Volume 123, Issue 1 (2017)
- Year:
- 2017
- Volume:
- 123
- Issue:
- 1
- Issue Sort Value:
- 2017-0123-0001-0000
- Page Start:
- S461
- Page End:
- S462
- Publication Date:
- 2017-05
- Subjects:
- Oncology -- Periodicals
Radiotherapy -- Periodicals
Tumors -- Periodicals
Medical Oncology -- Periodicals
Neoplasms -- radiotherapy -- Periodicals
Radiotherapy -- Periodicals
Radiothérapie -- Périodiques
Cancérologie -- Périodiques
Tumeurs -- Périodiques
Electronic journals
616.9940642 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01678140 ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01678140 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01678140 ↗
http://www.estro.org/ ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/radiotherapy-and-oncology/ ↗ - DOI:
- 10.1016/S0167-8140(17)31288-4 ↗
- Languages:
- English
- ISSNs:
- 0167-8140
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7240.790000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2884.xml