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Identifying Robust Radiomics Features for Lung Cancer by Using In-Vivo and Phantom Lung Lesions
We propose a novel framework for determining radiomics feature robustness by considering the effects of both biological and noise signals. This framework is preliminarily tested in a study predicting the epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) pa...
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| 出版年: | Tomography |
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| 主要な著者: | , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI
2021
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7934702/ https://ncbi.nlm.nih.gov/pubmed/33681463 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/tomography7010005 |
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