Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study.
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| Title: | Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. |
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| Authors: | Dou Q; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China. qdou@cse.cuhk.edu.hk., So TY; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China., Jiang M; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China., Liu Q; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China., Vardhanabhuti V; Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China., Kaissis G; Biomedical Image Analysis Group, Imperial College London, London, UK.; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.; OpenMined, Oxford, UK., Li Z; Biomedical Image Analysis Group, Imperial College London, London, UK., Si W; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China., Lee HHC; Department of Diagnostic Radiology, Princess Margaret Hospital, Hong Kong SAR, China., Yu K; Department of Radiology, Tuen Muen Hospital, Hong Kong SAR, China., Feng Z; Department of Emergency Medicine, Peking University ShenZhen Hospital, Shenzhen, Guangdong, China., Dong L; Department of Radiology, Zhijiang People's Hospital, Zhijiang, Hubei, China., Burian E; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany., Jungmann F; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany., Braren R; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.; German Cancer Research Center (DKFZ), Heidelberg, Germany., Makowski M; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany., Kainz B; Biomedical Image Analysis Group, Imperial College London, London, UK., Rueckert D; Biomedical Image Analysis Group, Imperial College London, London, UK.; AI in Medicine and Healthcare, Technical University of Munich, School of Informatics and Medicine, Munich, Germany., Glocker B; Biomedical Image Analysis Group, Imperial College London, London, UK. b.glocker@imperial.ac.uk., Yu SCH; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China. simonyu@cuhk.edu.hk., Heng PA; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China. pheng@cse.cuhk.edu.hk. |
| Source: | NPJ digital medicine [NPJ Digit Med] 2022 Apr 24; Vol. 5 (1), pp. 56. Date of Electronic Publication: 2022 Apr 24. |
| Publication Type: | Published Erratum |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| FullText | Text: Availability: 0 |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 35462562 AccessLevel: 2 PubTypeId: unknown PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Dou+Q%22">Dou Q</searchLink>; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China. qdou@cse.cuhk.edu.hk.<br /><searchLink fieldCode="AU" term="%22So+TY%22">So TY</searchLink>; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Jiang+M%22">Jiang M</searchLink>; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Liu+Q%22">Liu Q</searchLink>; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Vardhanabhuti+V%22">Vardhanabhuti V</searchLink>; Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Kaissis+G%22">Kaissis G</searchLink>; Biomedical Image Analysis Group, Imperial College London, London, UK.; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.; OpenMined, Oxford, UK.<br /><searchLink fieldCode="AU" term="%22Li+Z%22">Li Z</searchLink>; Biomedical Image Analysis Group, Imperial College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Si+W%22">Si W</searchLink>; Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.<br /><searchLink fieldCode="AU" term="%22Lee+HHC%22">Lee HHC</searchLink>; Department of Diagnostic Radiology, Princess Margaret Hospital, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Yu+K%22">Yu K</searchLink>; Department of Radiology, Tuen Muen Hospital, Hong Kong SAR, China.<br /><searchLink fieldCode="AU" term="%22Feng+Z%22">Feng Z</searchLink>; Department of Emergency Medicine, Peking University ShenZhen Hospital, Shenzhen, Guangdong, China.<br /><searchLink fieldCode="AU" term="%22Dong+L%22">Dong L</searchLink>; Department of Radiology, Zhijiang People's Hospital, Zhijiang, Hubei, China.<br /><searchLink fieldCode="AU" term="%22Burian+E%22">Burian E</searchLink>; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22Jungmann+F%22">Jungmann F</searchLink>; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22Braren+R%22">Braren R</searchLink>; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.; German Cancer Research Center (DKFZ), Heidelberg, Germany.<br /><searchLink fieldCode="AU" term="%22Makowski+M%22">Makowski M</searchLink>; Institute for Diagnostic and Interventional Radiology, Technical University of Munich, School of Medicine, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22Kainz+B%22">Kainz B</searchLink>; Biomedical Image Analysis Group, Imperial College London, London, UK.<br /><searchLink fieldCode="AU" term="%22Rueckert+D%22">Rueckert D</searchLink>; Biomedical Image Analysis Group, Imperial College London, London, UK.; AI in Medicine and Healthcare, Technical University of Munich, School of Informatics and Medicine, Munich, Germany.<br /><searchLink fieldCode="AU" term="%22Glocker+B%22">Glocker B</searchLink>; Biomedical Image Analysis Group, Imperial College London, London, UK. b.glocker@imperial.ac.uk.<br /><searchLink fieldCode="AU" term="%22Yu+SCH%22">Yu SCH</searchLink>; Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China. simonyu@cuhk.edu.hk.<br /><searchLink fieldCode="AU" term="%22Heng+PA%22">Heng PA</searchLink>; Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China. pheng@cse.cuhk.edu.hk. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22101731738%22">NPJ digital medicine</searchLink> [NPJ Digit Med] 2022 Apr 24; Vol. 5 (1), pp. 56. <i>Date of Electronic Publication: </i>2022 Apr 24. – Name: TypePub Label: Publication Type Group: TypPub Data: Published Erratum – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Nature+Publishing+Group%22">Nature Publishing Group </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101731738 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2398-6352 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2223986352%22">23986352 </searchLink><i>NLM ISO Abbreviation: </i>NPJ Digit Med <i>Subsets: </i>PubMed not MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=35462562 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/s41746-022-00600-1 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 56 Titles: – TitleFull: Author Correction: Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dou Q – PersonEntity: Name: NameFull: So TY – PersonEntity: Name: NameFull: Jiang M – PersonEntity: Name: NameFull: Liu Q – PersonEntity: Name: NameFull: Vardhanabhuti V – PersonEntity: Name: NameFull: Kaissis G – PersonEntity: Name: NameFull: Li Z – PersonEntity: Name: NameFull: Si W – PersonEntity: Name: NameFull: Lee HHC – PersonEntity: Name: NameFull: Yu K – PersonEntity: Name: NameFull: Feng Z – PersonEntity: Name: NameFull: Dong L – PersonEntity: Name: NameFull: Burian E – PersonEntity: Name: NameFull: Jungmann F – PersonEntity: Name: NameFull: Braren R – PersonEntity: Name: NameFull: Makowski M – PersonEntity: Name: NameFull: Kainz B – PersonEntity: Name: NameFull: Rueckert D – PersonEntity: Name: NameFull: Glocker B – PersonEntity: Name: NameFull: Yu SCH – PersonEntity: Name: NameFull: Heng PA IsPartOfRelationships: – BibEntity: Dates: – D: 24 M: 04 Text: 2022 Apr 24 Type: published Y: 2022 Identifiers: – Type: issn-electronic Value: 2398-6352 Numbering: – Type: volume Value: 5 – Type: issue Value: 1 Titles: – TitleFull: NPJ digital medicine Type: main |
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