Identification of COVID-19 with Chest X-ray images using Deep learning

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PUNAM KHANDAR
CHETANA THAOKAR

Abstract

Covid-19 had become an outbreak at the end of December 2019, it has become a nightmare for all. It resulted in
a huge loss in the health, life and economic sector of a country. It is a common spreading disease. Its symptoms
are similar to pneumonia, which make it very hard to distinguish. After a clinical study of COVID-19 infected
patients, it is discovered that infected patients tend to have a lung infection after getting in contact with the virus.
Chest X-ray and CT scans are the most widely used techniques for detecting lung related problems. As many
countries are economically deprived after this situation, Chest X-ray is opted over CT scan, as the X-ray is less
expensive, fast and simple than CT scans. In the health sector, deep learning has always been a very effective
technique. Numerous sources of medical images help deep learning to improvise itself and help this technique
to combat COVID-19 outbreak. In this paper, we have described the dataset and model formulation. Then we
provided the comparison and analysis of models those we have used for the experimentation purpose. It describes
the implementation of each model and their comparison on the basis of loss and accuracy. Finally, we have
mentioned the results and discussion along with the future scopes that we hope to cover later on.

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How to Cite
KHANDAR, P., & THAOKAR, C. (2021). Identification of COVID-19 with Chest X-ray images using Deep learning. International Journal of Next-Generation Computing, 12(5). https://doi.org/10.47164/ijngc.v12i5.465

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