Meng, Fanyang
Kottlors, Jonathan
Shahzad, Rahil
Liu, Haifeng
Fervers, Philipp
Jin, Yinhua
Rinneburger, Miriam
Le, Dou
Weisthoff, Mathilda
Liu, Wenyun
Ni, Mengzhe
Sun, Ye
An, Liying
Huai, Xiaochen
Móré, Dorottya
Giannakis, Athanasios
Kaltenborn, Isabel
Bucher, Andreas
Maintz, David
Zhang, Lei
Thiele, Frank
Li, Mingyang
Perkuhn, Michael
Zhang, Huimao
Persigehl, Thorsten
Funding for this research was provided by:
Sino-German Center for Research Promotion (SGC), a project entitled CT-based Deep Learning Algorithm in Diagnosis and evaluation of COVID-19:An International Multi-center Study (C-0007, C-0007)
Jilin Provincial Key Laboratory of Medical imaging & big data (20200601003JC)
Radiology and Technology Innovation Center of Jilin Province (20190902016TC)
China International Medical Foundation,Imaging Research,SKY (Z-2014-07-2003-03)
RACOON (NUM), under BMBF (01KX2021)
Article History
Received: 28 May 2022
Revised: 3 November 2022
Accepted: 29 November 2022
First Online: 16 December 2022
Declarations
:
: The scientific guarantors of this publication are Huimao ZHANG (Department of Radiology, The First Hospital of Ji Lin University, Changchun, China) and Thorsten Persigehl (Diagnostic and Interventional Radiology, University Hospital Cologne, Germany)
: Rahil Shahzad, Frank Thiele, Michael Perkuhn, Xiaochen Huai are employees of Philips Healthcare, other authors declare no conflicts of interest and had full control over all data and guarantee for correctness.
: Two of the authors (Jonathan Kottlors and Rahil Shahzad) have significant statistical expertise.
: The study is on human subjects: Written informed consent was waived by the Institutional Review Board.
: This retrospective study received ethical approval and informed consent was waived at all participating hospitals (Jilin: 2020-595, Wuhan: [2020]17, Ningbo: PJ-NBEY-KY-2020-194-01, Cologne: 20-1676, Frankfurt: 20-719, and Heidelberg: S-293/2020).
: • retrospective• diagnostic or prognostic study• multicenter study
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