An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors.

Longxi Zhou; Xianglin Meng; Yuxin Huang; Kai Kang; Juexiao Zhou; Yuetan Chu; Haoyang Li; Dexuan Xie; Jiannan Zhang; Weizhen Yang; Na Bai; Yi Zhao; Mingyan Zhao; Guohua Wang; Lawrence Carin; Xigang Xiao; Kaijiang Yu; Zhaowen Qiu; Xin Gao

doi:10.1038/s42256-022-00483-7

An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors.

Longxi Zhou, Xianglin Meng, Yuxin Huang, Kai Kang, Juexiao Zhou, Yuetan Chu, Haoyang Li, Dexuan Xie, Jiannan Zhang, Weizhen Yang, Na Bai, Yi Zhao, Mingyan Zhao, Guohua Wang, Lawrence Carin, Xigang Xiao, Kaijiang Yu, Zhaowen Qiu, Xin Gao

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Original language	English (US)
Pages (from-to)	494-503
Number of pages	10
Journal	Nat. Mach. Intell.
Volume	4
Issue number	5
DOIs	https://doi.org/10.1038/s42256-022-00483-7
State	Published - 2022

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10.1038/s42256-022-00483-7

Cite this

Zhou, L., Meng, X., Huang, Y., Kang, K., Zhou, J., Chu, Y., Li, H., Xie, D., Zhang, J., Yang, W., Bai, N., Zhao, Y., Zhao, M., Wang, G., Carin, L., Xiao, X., Yu, K., Qiu, Z., & Gao, X. (2022). An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors. Nat. Mach. Intell., 4(5), 494-503. https://doi.org/10.1038/s42256-022-00483-7

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title = "An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors.",

author = "Longxi Zhou and Xianglin Meng and Yuxin Huang and Kai Kang and Juexiao Zhou and Yuetan Chu and Haoyang Li and Dexuan Xie and Jiannan Zhang and Weizhen Yang and Na Bai and Yi Zhao and Mingyan Zhao and Guohua Wang and Lawrence Carin and Xigang Xiao and Kaijiang Yu and Zhaowen Qiu and Xin Gao",

year = "2022",

doi = "10.1038/s42256-022-00483-7",

language = "English (US)",

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Zhou, L, Meng, X, Huang, Y, Kang, K, Zhou, J, Chu, Y, Li, H, Xie, D, Zhang, J, Yang, W, Bai, N, Zhao, Y, Zhao, M, Wang, G, Carin, L, Xiao, X, Yu, K, Qiu, Z & Gao, X 2022, 'An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors.', Nat. Mach. Intell., vol. 4, no. 5, pp. 494-503. https://doi.org/10.1038/s42256-022-00483-7

TY - JOUR

T1 - An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors.

AU - Zhou, Longxi

AU - Meng, Xianglin

AU - Huang, Yuxin

AU - Kang, Kai

AU - Zhou, Juexiao

AU - Chu, Yuetan

AU - Li, Haoyang

AU - Xie, Dexuan

AU - Zhang, Jiannan

AU - Yang, Weizhen

AU - Bai, Na

AU - Zhao, Yi

AU - Zhao, Mingyan

AU - Wang, Guohua

AU - Carin, Lawrence

AU - Xiao, Xigang

AU - Yu, Kaijiang

AU - Qiu, Zhaowen

AU - Gao, Xin

PY - 2022

Y1 - 2022

U2 - 10.1038/s42256-022-00483-7

DO - 10.1038/s42256-022-00483-7

M3 - Article

VL - 4

SP - 494

EP - 503

JO - Nat. Mach. Intell.

JF - Nat. Mach. Intell.

IS - 5

ER -