Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
About this item
Full title
Author / Creator
Publisher
United States: Public Library of Science
Journal title
Language
English
Formats
Publication information
Publisher
United States: Public Library of Science
Subjects
More information
Scope and Contents
Contents
Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical courses and outcomes, even within the same tumor stage. This study explores deep learning applications in medical imaging allowing for the automated quantification of radiographic characteristics and potentially improving patient stratification.
We performed an integr...
Alternative Titles
Full title
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_plos_journals_2252264681
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2252264681
Other Identifiers
ISSN
1549-1676,1549-1277
E-ISSN
1549-1676
DOI
10.1371/journal.pmed.1002711
