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Delineating COVID-19 subgroups using routine clinical data identifies distinct in-hospital outcomes.

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第一作者： Bojidar,Rangelov

第一单位： Satsuma Lab, Centre for Medical Image Computing (CMIC), University College London, London, UK. dar.rangelov@gmail.com.

作者： Bojidar,Rangelov ^[1] ; Alexandra,Young ^[2] ; Watjana,Lilaonitkul ^[3] ; Shahab,Aslani ^[4] ; Paul,Taylor ^[3] ; Eyjólfur,Guðmundsson ^[4] ; Qianye,Yang ^[5] ; Yipeng,Hu ^[6] ; John R,Hurst ^[7] ; David J,Hawkes ^[8] ; Joseph,Jacob ^[4] ; Тhe NCCID Collaborative

作者单位： Satsuma Lab, Centre for Medical Image Computing (CMIC), University College London, London, UK. dar.rangelov@gmail.com. ^[1] Satsuma Lab, Centre for Medical Image Computing (CMIC), University College London, London, UK.;Department of Neuroimaging, King's College London, London, UK. ^[2] Institute of Health Informatics, University College London, London, UK. ^[3] Satsuma Lab, Centre for Medical Image Computing (CMIC), University College London, London, UK. ^[4] Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK. ^[5] Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London, UK.;Centre for Medical Image Computing, University College London, London, UK. ^[6] UCL Respiratory, University College London, London, UK. ^[7] Centre for Medical Image Computing, University College London, London, UK. ^[8]

医学主题词人类(Humans);疾病大流行(Pandemics);医院(Hospitals);预测(Forecasting)

DOI 10.1038/s41598-023-32469-9

PMID 37339958

发布时间 2025-05-30

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