The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer-Reference-Cited by-同舟云学术

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The impact of high-order features on performance of radiomics studies in CT non-small cell lung cancer

Published:2024-09 Issue: Volume:113 Page:110244
ISSN:0899-7071
Container-title:Clinical Imaging
language:en
Short-container-title:Clinical Imaging

Author:

Ge Gary^ORCID,Zhang Jason Z^ORCID,Zhang Jie^ORCID

Publisher

Elsevier BV

Reference9 articles.

1. Radiomics: images are more than pictures, they are data;Gillies;Radiology,2016

2. Radiomics: a new application from established techniques;Parekh;Expert Rev Precis Med Drug Dev,2016

3. Optimal number of features as a function of sample size for various classification rules;Hua;Bioinformatics,2004

4. Feature selection methods and predictive models in CT lung cancer radiomics;Ge;J Appl Clin Med Phys,2023

5. radiomics;Hansen,2017

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