COVID-19 Phenotypes and Comorbidity: A Data-Driven, Pattern Recognition Approach Using National Representative Data from the United States.

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第一作者： George D,Vavougios

第一单位： Department of Neurology, University of Cyprus, 75 Kallipoleos Street, Lefkosia 1678, Cyprus.

作者： George D,Vavougios ^[1] ; Vasileios T,Stavrou ^[2] ; Christoforos,Konstantatos ^[3] ; Pavlos-Christoforos,Sinigalias ^[2] ; Sotirios G,Zarogiannis ^[4] ; Konstantinos,Kolomvatsos ^[5] ; George,Stamoulis ^[3] ; Konstantinos I,Gourgoulianis ^[6]

作者单位： Department of Neurology, University of Cyprus, 75 Kallipoleos Street, Lefkosia 1678, Cyprus. ^[1] Laboratory of Cardio-Pulmonary Testing and Pulmonary Rehabilitation, Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, Biopolis, 41500 Larissa, Greece. ^[2] Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopolis, 41500 Larissa, Greece. ^[3] Department of Business Administration, University of Patras, University Campus-Rio, 26504 Patras, Greece. ^[4] Department of Mechanical Engineering and Aeronautics, University of Patras, 26504 Patras, Greece. ^[5] Department of Physiology, Faculty of Medicine, School of Health Sciences, University of Thessaly, Biopois, 41500 Larissa, Greece. ^[6] Department of Electrical and Computer Engineering, University of Thessaly, 37 Glavani-28th October Str., Deligiorgi Building, 4th Floor, 38221 Volos, Greece. ^[7]

关键词 COVID-19 big data comorbidity epidemiology pattern recognition phenotypes

主题词共病现象(Comorbidity);咳嗽(Cough);人类(Humans);表型(Phenotype);美国(United States)

DOI 10.3390/ijerph19084630

PMID 35457497

发布时间 2023-03-08

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