Preselection of robust radiomic features does not improve outcome modelling in non-small cell lung cancer based on clinical routine FDG-PET imaging

Preselection of robust radiomic features does not improve outcome modelling in non-small cell lung cancer based on clinical routine FDG-PET imaging

Abstract Background Radiomics is a promising tool for identifying imaging-based biomarkers. Radiomics-based models are often trained on single-institution datasets; however, multi-centre imaging datasets are preferred for external generalizability owing to the influence of inter-institutional scanni...

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Bibliographic Details
Main Authors: Carol Oliveira, Florian Amstutz, Diem Vuong, Marta Bogowicz, Martin Hüllner, Robert Foerster, Lucas Basler, Christina Schröder, Eric I. Eboulet, Miklos Pless, Sandra Thierstein, Solange Peters, Sven Hillinger, Stephanie Tanadini-Lang, Matthias Guckenberger
Format: Article
Language:English
Published: SpringerOpen 2021-08-01
Series:EJNMMI Research
Subjects:
Multi-centre
Radiomics
Lung cancer
PET
Robust
Online Access:https://doi.org/10.1186/s13550-021-00809-3

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