A deep learning model for prediction of post hepatectomy liver failure after hemihepatectomy using preoperative contrast-enhanced computed tomography: a retrospective study.

Xu, Xiaoqing; Xing, Zijian; Xu, Zhiyao; Tong, Yifan; Wang, Shuxin; Liu, Xiaoqing; Ren, Yiyue; Liang, Xiao; Yu, Yizhou; Ying, Hanning

Xu, Xiaoqing; Xing, Zijian; Xu, Zhiyao; Tong, Yifan; Wang, Shuxin; Liu, Xiaoqing; Ren, Yiyue; Liang, Xiao; Yu, Yizhou; Ying, Hanning.

Afiliación

Xu X; Department of Nursing, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xing Z; Deepwise Artificial Intelligence Laboratory, Hangzhou, China.
Xu Z; Department of Pathology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Tong Y; Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Wang S; Deepwise Artificial Intelligence Laboratory, Hangzhou, China.
Liu X; Deepwise Artificial Intelligence Laboratory, Hangzhou, China.
Ren Y; Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Liang X; Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yu Y; Faculty of Engineering, The University of Hong Kong, Hong Kong, China.
Ying H; Department of General Surgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Front Med (Lausanne) ; 10: 1154314, 2023.

Article en En | MEDLINE | ID: mdl-37448800

Palabras clave

contrast enhanced CT; deep learning; hemihepatectomy; liver failure; prediction model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Med (Lausanne) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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