A machine-learning-based combination of criteria to detect bladder cancer lymph node metastasis on [...
A machine-learning-based combination of criteria to detect bladder cancer lymph node metastasis on [18F]FDG PET/CT: a pathology-controlled study
About this item
Full title
Author / Creator
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
Objectives
Initial pelvic lymph node (LN) staging is pivotal for treatment planification in patients with muscle-invasive bladder cancer (MIBC), but [
18
F]FDG PET/CT provides insufficient and variable diagnostic performance. We aimed to develop and validate a machine-learning-based combination of criteria on [
18
F]FDG PET/CT to acc...
Alternative Titles
Full title
A machine-learning-based combination of criteria to detect bladder cancer lymph node metastasis on [18F]FDG PET/CT: a pathology-controlled study
Authors, Artists and Contributors
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Record Identifier
TN_cdi_proquest_miscellaneous_2739740608
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2739740608
Other Identifiers
ISSN
1432-1084,0938-7994
E-ISSN
1432-1084
DOI
10.1007/s00330-022-09270-9
