Cargando…
A deep learning integrated radiomics model for identification of coronavirus disease 2019 using computed tomography
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 of COVID...
Autores principales: | Zhang, Xiaoguo, Wang, Dawei, Shao, Jiang, Tian, Song, Tan, Weixiong, Ma, Yan, Xu, Qingnan, Ma, Xiaoman, Li, Dasheng, Chai, Jun, Wang, Dingjun, Liu, Wenwen, Lin, Lingbo, Wu, Jiangfen, Xia, Chen, Zhang, Zhongfa |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886892/ https://www.ncbi.nlm.nih.gov/pubmed/33594159 http://dx.doi.org/10.1038/s41598-021-83237-6 |
Ejemplares similares
-
Severe acute respiratory syndrome coronavirus 2 viral load in respiratory and feces specimens of children with coronavirus disease 2019
por: Ma, Xiang, et al.
Publicado: (2021) -
Diagnostic value and key features of computed tomography in Coronavirus Disease 2019
por: Li, Bingjie, et al.
Publicado: (2020) -
CT-based radiomics for predicting the rapid progression of coronavirus disease 2019 (COVID-19) pneumonia lesions
por: Zhang, Bin, et al.
Publicado: (2021) -
Clinical and computed tomography features in patients with coronavirus disease 2019
por: Wang, Dongxu, et al.
Publicado: (2021) -
Toward the determination of sensitive and reliable whole-lung computed tomography features for robust standard radiomics and delta-radiomics analysis in a nonhuman primate model of coronavirus disease 2019
por: Castro, Marcelo A., et al.
Publicado: (2022)