Interpretatively automated identification of circulating tumor cells from human peripheral blood with high performance.

Li, Xiaolei; Chen, Mingcan; Xu, Jingjing; Wu, Dihang; Ye, Mengxue; Wang, Chi; Liu, Wanyu

Li, Xiaolei; Chen, Mingcan; Xu, Jingjing; Wu, Dihang; Ye, Mengxue; Wang, Chi; Liu, Wanyu.

Afiliación

Li X; Sino-European School of Technology of Shanghai University, Shanghai University, Shanghai, China.
Chen M; Sino-European School of Technology of Shanghai University, Shanghai University, Shanghai, China.
Xu J; Sino-European School of Technology of Shanghai University, Shanghai University, Shanghai, China.
Wu D; Sino-European School of Technology of Shanghai University, Shanghai University, Shanghai, China.
Ye M; Sino-European School of Technology of Shanghai University, Shanghai University, Shanghai, China.
Wang C; School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China.
Liu W; Sino-European School of Technology of Shanghai University, Shanghai University, Shanghai, China.

Front Bioeng Biotechnol ; 11: 1013107, 2023.

Article en En | MEDLINE | ID: mdl-36845198

Palabras clave

circulating tumor cells; deep learning; interpretative analysis; precise identification; single-shot multibox detector

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Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Screening_studies Idioma: En Revista: Front Bioeng Biotechnol Año: 2023 Tipo del documento: Article

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