COVID-DETECT: A Deep Learning Based Approach to Accelerate COVID-19 Detection

After two years of COVID-19 first infection and its speedy
propagation, death and infection cases are till exponentially increasing.
Unfortunately, during this a non-fully controlled situation, we noticed that
the existing solutions for COVID-19 detection based on chest X-ray were
not reliable enough in relation to the number of infected patients and the
severity of the outbreak. To handle this issue by increasing the reliability
and the efficiency of COVID-19 detection, we therefore deploy and compare
the results of a set of reconfigurable classification approaches and
deep learning techniques. Indeed, we have achieved a score of up to 99% AQ1
accuracy with a dataset of 15,000 X-ray images, which makes the selected
detection technique, deep learning, more reliable and effective.