Abstract
The world came to a standstill in 2020 when a virus, SARS-CoV-2 started infecting people, and more shockingly was deadly. Lockdowns were enforced all over the world. Social distancing and self-quarantine became the need of the hour to prevent oneself from succumbing to this virus. One major concern regarding this disease was its detection since the disease was contagious and had a large incubation period. Reverse Transmission Polymerase Chain Reaction tests (RT-PCR) were used commonly but were often showing false negatives, leading to further transmission as soon as the patient was discharged. However, radiographic analysis including methods such as chest X-rays or Computed Tomography (CT) scans led the race of revealing with the highest accuracy, and reliability, if an infected patient who was with or without symptoms, was a victim to this lethal syndrome. We demonstrate a study over how CT scans and chest X-rays are beneficial for the detection of the COVID-19 virus using advanced Artificial Intelligence (AI) technologies, and we used the deep learning algorithm Convolutional Neural Networks (CNN) using Tensorflow and Keras for radiology image classification of X-rays and CT scans. These are highly advantageous as they detect the development of COVID-19, as well as other critical ailments like various types of pneumonia. This transfer learning approach successfully detected chest X-ray and CT scan patterns and showed precise medical diagnostics with high levels of accuracy up to 89% while detecting SARS-CoV-2.
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Trivedi, D., Dave, M., Patel, R., Dave, V., Rathod, G. (2021). Real-Time COVID-19 Detection and Prediction Using Chest X-rays and CT Scan: A Comparative Study Using AI. In: Gao, XZ., Kumar, R., Srivastava, S., Soni, B.P. (eds) Applications of Artificial Intelligence in Engineering. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-4604-8_60
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DOI: https://doi.org/10.1007/978-981-33-4604-8_60
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