Non-contact advanced method of COVID-19 classification using deep learning with chest x-ray images

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Shagufta Samreen
Vishwanth R h


The first appearance of the novel coronavirus (COVID-19) was on December 31st 2019, in the Wuhan City of China. This novel coronavirus (COVID-19) spread rapidly around the world, thus causing a pandemic. The most devastating effect was caused on the daily lives, global economy and public health system. In order to treat the affected patients quickly the most critical step is to detect the positive cases in much advance period of time in order to help prevent further spread of this disease. With the help of the recent findings, it has been found that the radiology imagining techniques contain the salient information about this virus. The advanced Artificial Intelligence (AI) technique coupled with this radiological imaging has found to be helpful for the accurate detection of this novel coronavirus (COVID-19) disease. This is an advanced application which is helpful for the study of this paper. In this study, the new model used for the detection of this coronavirus (COVID-19) by using the raw chest X-ray images automatically. This proposed model provides accurate diagnostics for binary classification (COVID-19 vs normal) and also the multi-class classification (COVID-19 vs Normal vs Pneumonia). The classification accuracy from this proposed model is about 98.09% for binary classes classification and 87.03% for multi-class classification.


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Siti Raih anah, Mohd Asyraf and Nuraisyah “A Leightweight Deep-learning model for COVID-19 detectionâ€proposed the SPP-COVID-NET method published in IEEE access,2020 IEEE symposium in Industrial application(ISIEA).

Tulin Ozturk , Talo,Ulas and Eylul Azra “Detection of COVID-19 using deep learning with x-ray images†published in NCBI 2020, vol 121:103792

Abdul Ella and Hassan Ella “COVID-19 diagonistics from chest X-rays published in NCBI in 2020 Vol 78:131-145.

Sohaib Asif, Wenhui, Jin, Tao and Si Jinhai “Classification of COVID-19 using chest X-rays published in Medrxiv in 2020, vol. 200882.

Wu F., Zhao S., Yu B. A new coronavirus associated with human respiratory disease in China. Nature. 2020;579(7798):265–269.

Huang C., Wang Y. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506.

World Health Organization (WHO); 2020. Pneumonia

Of unknown cause-china emergenices,prepardnes

Response, Disease Outbreak News

Wu Z., McGoogan J.M. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. Jama. 2020;323(13):1239–1242.

Holshue M.L., DeBolt C. First case of 2019 novel coronavirus in the United States. N. Engl. J. Med. 2020;328:929–936.

Kanne J.P., Little B.P., Chung J.H., Elicker B.M., Ketai L.H. Essentials for radiologists on COVID-19: an update—radiology scientific expert panel. Radiology. 2020 doi: 10.1148/radiol.2020200527.

Kong W., Agarwal P.P. Chest imaging appearance of COVID-19 infection.

Ashwinkumar.U.M and Dr. Anandakumar K.R, "Predicting Early Detection of cardiac and Diabetes symptoms using Data mining techniques", International conference on computer Design and Engineering, vol.49, 2012

Singhal T. A review of coronavirus disease-2019 (COVID-19) Indian J. Pediatr. 2020;87:281– 286.

Zu Z,Jiang M.D, Xu P.P, Chen W, Ni Q.Q, Lu G.M, Zhang L.J. Coronavirus disease 2019 (COVID-19): a perspective from China. Radiology. 2020 doi: 10.1148/radiol.2020200490.