Deep learning-based overall survival prediction model in patients with rare cancer: a case study for primary central nervous system lymphoma.
Saved in:
| Title: | Deep learning-based overall survival prediction model in patients with rare cancer: a case study for primary central nervous system lymphoma. |
|---|---|
| Authors: | She Z; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy. ziyu.she@polimi.it., Marzullo A; Department of Mathematics and Computer Science, University of Calabria, Rende, Italy., Destito M; Department of Experimental and Clinical Medicine, University of Catanzaro, Catanzaro, Italy., Spadea MF; Department of Experimental and Clinical Medicine, University of Catanzaro, Catanzaro, Italy., Leone R; Neuroradiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy., Anzalone N; Neuroradiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy., Steffanoni S; Lymphoma Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy., Erbella F; Lymphoma Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy., Ferreri AJM; Lymphoma Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy., Ferrigno G; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy., Calimeri T; Lymphoma Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy., De Momi E; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy. |
| Source: | International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2023 Oct; Vol. 18 (10), pp. 1849-1856. Date of Electronic Publication: 2023 Apr 21. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Germany NLM ID: 101499225 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1861-6429 (Electronic) Linking ISSN: 18616410 NLM ISO Abbreviation: Int J Comput Assist Radiol Surg Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1861-6429 |
|---|---|
| DOI: | 10.1007/s11548-023-02886-2 |
