COVID-19 is a contagious infection that has severe effects on the global economy and our daily life.Accurate diagnosis of COVID-19 is of importance for consultants,patients,and radiologists.In this study,we use the deep learn-ing network AlexNet as the backbone,and enhance it with the following two aspects:1)adding batch normalization to help accelerate the training,reducing the internal covariance shift;2)replacing the fully connected layer in AlexNet with three classifiers:SNN,ELM,and RVFL.Therefore,we have three novel models from the deep COVID network(DC-Net)framework,which are named DC-Net-S,DC-Net-E,and DC-Net-R,respectively.After comparison,we find the proposed DC-Net-R achieves an average accuracy of 90.91％on a private dataset(available upon email request)comprising of 296 images while the specificity reaches 96.13％,and has the best performance among all three proposed classifiers.In addition,we show that our DC-Net-R also performs much better than other existing algorithms in the literature.

Xin Zhang;Siyuan Lu;Shui-Hua Wang;Xiang Yu;Su-Jing Wang;Lun Yao;Yi Pan;Yu-Dong Zhang

Department of Medical Imaging,The Fourth People's Hospital of Huai'an,Huai'an 223002,China;School of Informatics,University of Leicester,Leicester,LE1 7RH,U.K.;School of Architecture Building and Civil Engineering,Loughborough University,Loughborough,LE11 3TU,U.K.;School of Mathematics and Actuarial Science,University of Leicester,Leicester,LE1 7RH,U.K.;Key Laboratory of Behavior Sciences,Institute of Psychology,Chinese Academy of Sciences,Beijing 100101,China;Department of Psychology,University of the Chinese Academy of Sciences,Beijing 100101,China;Department of Infection Diseases,The Fourth People's Hospital of Huai'an,Huai'an 223002,China;Department of Computer Science,Georgia State University,Atlanta 30302-5060,U.S.A.;Department of Information Systems,Faculty of Computing and Information Technology,King Abdulaziz University Jeddah 21589,Saudi Arabia

计算机科学技术学报（英文版）

[1]Xin Zhang;Siyuan Lu;Shui-Hua Wang;Xiang Yu;Su-Jing Wang;Lun Yao;Yi Pan;Yu-Dong Zhang-.Diagnosis of COVID-19 Pneumonia via a Novel Deep Learning Architecture)[J].计算机科学技术学报（英文版）,2022(02):330-343

Diagnosis,Pneumonia,via,Novel,Deep,Learning,Architecture,contagious,infection,that,has,severe,effects,global,economy,our,daily,life,Accurate,diagnosis,importance,consultants,patients,radiologists,In,this,study,we,use,deep,learn,network,AlexNet,backbone,enhance,following,aspects,adding,batch,normalization,help,accelerate,training,reducing,internal,covariance,shift,replacing,fully,connected,layer,three,classifiers,SNN,ELM,RVFL,Therefore,have,novel,models,from,DC,framework,which,are,named,respectively,After,comparison,find,proposed,achieves,average,accuracy,private,dataset,available,upon,email,request,comprising,images,while,specificity,reaches,best,performance,among,all,addition,show,also,performs,much,better,than,other,existing,algorithms,literature

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