An ordinal radiomic model to predict the differentiation grade of invasive non-mucinous pulmonary adenocarcinoma based on low-dose computed tomography in lung cancer screening.

Detalles Bibliográficos
Publicado en:European Radiology Vol. 33; no. 5; pp. 3072 - 3083
Autores principales: Li, Yong, Liu, Jieke, Yang, Xi, Wang, Ai, Zang, Chi, Wang, Lu, He, Changjiu, Lin, Libo, Qing, Haomiao, Ren, Jing, Zhou, Peng
Formato: Journal Article
Publicado: Springer Nature May2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: An ordinal radiomic model to predict the differentiation grade of invasive non-mucinous pulmonary adenocarcinoma based on low-dose computed tomography in lung cancer screening.
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          Li, Yong
          Liu, Jieke
          Yang, Xi
          Wang, Ai
          Zang, Chi
          Wang, Lu
          He, Changjiu
          Lin, Libo
          Qing, Haomiao
          Ren, Jing
          Zhou, Peng
        affil: Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, No. 55, Section 4, South Renmin Road, 610041, Chengdu, Sichuan, China
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      doctype: Journal Article
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    language: English
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