Woan Ching Serena Low, Joon Huang Chuah, Clarence Augustine T. H. Tee, Shazia Anis, Muhammad Ali Shoaib, Amir Faisal, Azira Khalil, Khin Wee Lai
Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infection endangering the lives of many people worldwide is the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19. This paper is aimed at detecting and differentiating viral pneumonia and COVID-19 disease using digital X-ray images. The current practices include tedious conventional processes that solely rely on the radiologist or medical consultant's technical expertise that are limited, time-consuming, inefficient, and outdated. The implementation is easily prone to human errors of being misdiagnosed. The development of deep learning and technology improvement allows medical scientists and researchers to venture into various neural networks and algorithms to develop applications, tools, and instruments that can further support medical radiologists. This paper presents an overview of deep learning techniques made in the chest radiography on COVID-19 and pneumonia cases. © 2021 Serena Low Woan Ching et al.
Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, 40603, Malaysia; Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, 40603, Malaysia; Department of Biomedical Engineering, Faculty of Production and Industrial Technology, Institut Teknologi Sumatera, Lampung, 35365, Indonesia; Faculty of Science and Technology, Universiti Sains Islam Malaysia, Nilai, Negeri Sembilan, 71800, Malaysia
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