Delta-radiomics features for the prediction of patient outcomes in non–small cell lung cancer
Abstract Radiomics is the use of quantitative imaging features extracted from medical images to characterize tumor pathology or heterogeneity. Features measured at pretreatment have successfully predicted patient outcomes in numerous cancer sites. This project was designed to determine whether radio...
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Auteurs principaux: | Xenia Fave, Lifei Zhang, Jinzhong Yang, Dennis Mackin, Peter Balter, Daniel Gomez, David Followill, Aaron Kyle Jones, Francesco Stingo, Zhongxing Liao, Radhe Mohan, Laurence Court |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2017
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Sujets: | |
Accès en ligne: | https://doaj.org/article/29380d9f555d4f32bed853ac2972c1e0 |
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