Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lu...
Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma
About this item
Full title
Author / Creator
Zhou, Linyi , Sun, Jinju , Long, He , Zhou, Weicheng , Xia, Renxiang , Luo, Yi , Fang, Jingqin , Wang, Yi and Chen, Xiao
Publisher
Vienna: Springer Vienna
Journal title
Language
English
Formats
Publication information
Publisher
Vienna: Springer Vienna
Subjects
More information
Scope and Contents
Contents
Objectives
To develop and validate a machine learning model using
18
F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma.
Methods
Eight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocar...
Alternative Titles
Full title
Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_2edb71cba1d04fdc9e191723e0568c81
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2edb71cba1d04fdc9e191723e0568c81
Other Identifiers
ISSN
1869-4101
E-ISSN
1869-4101
DOI
10.1186/s13244-023-01573-9
