Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal...
Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type
About this item
Full title
Author / Creator
Guo, Rui , Hu, Xiaobin , Song, Haoming , Xu, Pengpeng , Xu, Haoping , Rominger, Axel , Lin, Xiaozhu , Menze, Bjoern , Li, Biao and Shi, Kuangyu
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
Purpose
To develop a weakly supervised deep learning (WSDL) method that could utilize incomplete/missing survival data to predict the prognosis of extranodal natural killer/T cell lymphoma, nasal type (ENKTL) based on pretreatment
18
F-FDG PET/CT results.
Methods
One hundred and sixty-seven patients with ENKTL who underwent pretreatm...
Alternative Titles
Full title
Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7896833
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7896833
Other Identifiers
ISSN
1619-7070
E-ISSN
1619-7089
DOI
10.1007/s00259-021-05232-3
