Enhanced and unenhanced: Radiomics models for discriminating between benign and malignant cystic renal masses on CT images: A multi-center study.

Huang, Lesheng; Feng, Wenhui; Lin, Wenxiang; Chen, Jun; Peng, Se; Du, Xiaohua; Li, Xiaodan; Liu, Tianzhu; Ye, Yongsong

Huang, Lesheng; Feng, Wenhui; Lin, Wenxiang; Chen, Jun; Peng, Se; Du, Xiaohua; Li, Xiaodan; Liu, Tianzhu; Ye, Yongsong.

Afiliação

Huang L; Department of Radiology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.
Feng W; Department of Radiology, Zhuhai People's Hospital, Zhuhai, China.
Lin W; Department of Radiology, Zhuhai People's Hospital, Zhuhai, China.
Chen J; Department of Radiology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.
Peng S; Department of Laboratory, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.
Du X; Department of Radiology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.
Li X; Department of Gynaecology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.
Liu T; Department of Radiology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.
Ye Y; Department of Radiology, Guangdong Provincial Hospital of Traditional Chinese Medicine, Zhuhai, China.

PLoS One ; 18(9): e0292110, 2023.

Article em En | MEDLINE | ID: mdl-37768941

Assuntos

Algoritmos; Artérias; Estudos Retrospectivos; Rim; Tomografia Computadorizada por Raios X

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Artérias / Algoritmos Tipo de estudo: Clinical_trials / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Ano de publicação: 2023 Tipo de documento: Article

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