A deep learning integrated radiomics model for identification of coronavirus disease 2019 using computed tomography

Abstract Since its first outbreak, Coronavirus Disease 2019 (COVID-19) has been rapidly spreading worldwide and caused a global pandemic. Rapid and early detection is essential to contain COVID-19. Here, we first developed a deep learning (DL) integrated radiomics model for end-to-end identification...

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Autores principales:	Xiaoguo Zhang, Dawei Wang, Jiang Shao, Song Tian, Weixiong Tan, Yan Ma, Qingnan Xu, Xiaoman Ma, Dasheng Li, Jun Chai, Dingjun Wang, Wenwen Liu, Lingbo Lin, Jiangfen Wu, Chen Xia, Zhongfa Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2bba194f8c524411b02bf0aa9361d075
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A deep learning integrated radiomics model for identification of coronavirus disease 2019 using computed tomography

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