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Impact of feature selection methods and subgroup factors on prognostic analysis with CT-based radiomics in non-small cell lung cancer patients
BACKGROUND: Radiomics is a new technology to noninvasively predict survival prognosis with quantitative features extracted from medical images. Most radiomics-based prognostic studies of non-small-cell lung cancer (NSCLC) patients have used mixed datasets of different subgroups. Therefore, we invest...
Autores principales: | Sugai, Yuto, Kadoya, Noriyuki, Tanaka, Shohei, Tanabe, Shunpei, Umeda, Mariko, Yamamoto, Takaya, Takeda, Kazuya, Dobashi, Suguru, Ohashi, Haruna, Takeda, Ken, Jingu, Keiichi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8086112/ https://www.ncbi.nlm.nih.gov/pubmed/33931085 http://dx.doi.org/10.1186/s13014-021-01810-9 |
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