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.

Afiliación

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 en En | MEDLINE | ID: mdl-37768941

Asunto(s)

Algoritmos; Arterias; Estudios Retrospectivos; Riñón; Tomografía Computarizada por Rayos X

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Arterias / Algoritmos Tipo de estudio: Clinical_trials / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: China

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