Rapid COVID-19 diagnosis using ensemble deep transfer learning models from chest radiographic images
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ORIGINAL RESEARCH
Rapid COVID‑19 diagnosis using ensemble deep transfer learning models from chest radiographic images Neha Gianchandani1 · Aayush Jaiswal1 · Dilbag Singh2 · Vijay Kumar3 · Manjit Kaur2 Received: 11 June 2020 / Accepted: 3 November 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes novel coronavirus disease (COVID-19) outbreak in more than 200 countries around the world. The early diagnosis of infected patients is needed to discontinue this outbreak. The diagnosis of coronavirus infection from radiography images is the fastest method. In this paper, two different ensemble deep transfer learning models have been designed for COVID-19 diagnosis utilizing the chest X-rays. Both models have utilized pre-trained models for better performance. They are able to differentiate COVID-19, viral pneumonia, and bacterial pneumonia. Both models have been developed to improve the generalization capability of the classifier for binary and multi-class problems. The proposed models have been tested on two well-known datasets. Experimental results reveal that the proposed framework outperforms the existing techniques in terms of sensitivity, specificity, and accuracy. Keywords COVID-19 · SARS-CoV-2 · Transfer learning · Chest X-ray · Ensemble models
1 Introduction The outbreak of novel coronavirus surprised the whole world. The disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is also known as COVID-19. According to the World Health Organization (WHO), more than fifteen million peoples are infected from this virus across 215 countries (Coronavirus Disease (COVID-19) 2020). 0.63 million deaths with 9.43 million recovered cases are reported globally by 23 July 2020. USA, Brazil, and India are severely affected with 4.1 million, 2.2 million, and 1.3 million active corona cases, respectively. Due to the communicable nature of this virus and inappropriate treatment, the early detection of an infected person * Manjit Kaur [email protected] 1
Department of Computer Science and Engineering, School of Computing and Information Technology, Manipal University Jaipur, Jaipur, Rajasthan 303007, India
2
Computer Science Engineering, School of Engineering and Applied Sciences, Bennett University, Greater Noida 201310, India
3
Department of Computer Science and Engineering, National Institute of Technology Hamirpur, Hamirpur, Himachal Pradesh 177005, India
is required to discontinue the coronavirus spread (Oh et al. 2020). The main source for detecting the infected person is symptoms developed in the patients. The infected person may suffer from fever, cough, breathing problem, sore throat, diarrhoea, and headache (COVID-19 symptoms 2020). Loss of smell, tiredness, disappearing of taste, and aches may be found in some patients. However, the presence of COVID19 symptoms may not be found in some infected persons (Loey et al. 2020). Due to this, the detection of an infected person is a
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