In view of the COVID-19 pandemic, the exponential increase in the COVID-19 patients is leading to the enormous demand on the healthcare systems across the world. The allocation of resources towards the detection of the people affected by the virus plays a key role in curbing the pandemic and slowing down the spread of the virus to a greater extent. While traditional procedures are utilized to discover COVID-19 individuals, testing each individual with a limited number of testing kits is a massive undertaking. Most healthcare systems include X-ray equipment, and most of them being digitized, can be utilized as a way of screening for COVID-19 patients. This paper proposes AI model that can analyze and predict a possible COVID-19 patient, which can be used to prioritize the people for further testing. Further we propose the automation of this process where the models can be deployed in a remote server or an edge computing device where the X-ray images can be screened by the deep learning model to give predictions with very less turnaround time.
CITATION STYLE
Jai Shankar, K. N., Poornima, G. R., & Narayanappa, C. K. (2022). COVID-19 Detection using Chest X-RAY. International Journal of Circuits, Systems and Signal Processing, 16, 859–864. https://doi.org/10.46300/9106.2022.16.105
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