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Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

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Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2608263086

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

About this item

Full title

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Author / Creator

Wang, Robin , Jiao, Zhicheng , Yang, Li , Choi, Ji Whae , Xiong, Zeng , Halsey, Kasey , Tran, Thi My Linh , Pan, Ian , Collins, Scott A. , Feng, Xue , Wu, Jing , Chang, Ken , Shi, Lin-Bo , Yang, Shuai , Yu, Qi-Zhi , Liu, Jie , Fu, Fei-Xian , Jiang, Xiao-Long , Wang, Dong-Cui , Zhu, Li-Ping , Yi, Xiao-Ping , Healey, Terrance T. , Zeng, Qiu-Hua , Liu, Tao , Hu, Ping-Feng , Huang, Raymond Y. , Li, Yi-Hui , Sebro, Ronnie A. , Zhang, Paul J. L. , Wang, Jianxin , Atalay, Michael K. , Liao, Wei-Hua , Fan, Yong and Bai, Harrison X.

Publisher

Berlin/Heidelberg: Springer Berlin Heidelberg

Journal title

European radiology, 2022-01, Vol.32 (1), p.205-212

Language

English

Formats

Articles

Publication information

Publisher

Berlin/Heidelberg: Springer Berlin Heidelberg

Subjects

More information

Scope and Contents

Contents

Objectives
Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients.
Metho...

Alternative Titles

Full title

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

Authors, Artists and Contributors

Author / Creator

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2608263086

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2608263086

Other Identifiers

ISSN

0938-7994

E-ISSN

1432-1084

DOI

10.1007/s00330-021-08049-8

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