Artificial intelligence computed tomography helps evaluate the severity of COVID-19 patients: A retrospective study.

Han, Yi; Mu, Su-Cheng; Zhang, Hai-Dong; Wei, Wei; Wu, Xing-Yue; Jin, Chao-Yuan; Gu, Guo-Rong; Xie, Bao-Jun; Tong, Chao-Yang

Han, Yi; Mu, Su-Cheng; Zhang, Hai-Dong; Wei, Wei; Wu, Xing-Yue; Jin, Chao-Yuan; Gu, Guo-Rong; Xie, Bao-Jun; Tong, Chao-Yang.

Afiliação

Han Y; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.
Mu SC; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.
Zhang HD; Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Wei W; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.
Wu XY; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.
Jin CY; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.
Gu GR; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.
Xie BJ; Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China.
Tong CY; Department of Emergency Medicine, Zhongshan Hospital Fudan University, Shanghai 200032, China.

World J Emerg Med ; 13(2): 91-97, 2022.

Article em En | MEDLINE | ID: mdl-35237361

Palavras-chave

Artificial intelligence; COVID-19; Chest computed tomography

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Idioma: En Revista: World J Emerg Med Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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