These previous studies focused on detect automated COVID-19 from X-ray images or CT images for patient lungs by using CNN and deep learning techniques and transfer learning. However, a few other studies to date have used cross-validation to check the accuracy and other performance metrics of their results. The current study introduces mechanisms based on deep learning and transfer of learning in order to detect covid 19 from x-ray images of the lungs, these mechanisms build on the mechanisms that were presented in the literature review, but K-fold Cross Validation was added in order to obtain a true accuracy of the system and calculated many of performance metrics which help in explaining the best pre-trained networks and the best classifier.
These previous studies focused on detect automated COVID-19 from X-ray images or CT images for patient lungs by using CNN and deep
learning
techniques and transfer
learning
.
However
, a few other studies to date have
used
cross-validation to
check
the accuracy and other performance metrics of their results. The
current
study introduces mechanisms based on deep
learning
and transfer of
learning
in order to detect
covid 19
from x-ray images of the lungs, these mechanisms build on the mechanisms that
were presented
in the literature review,
but
K-fold Cross Validation was
added
in order to obtain a true accuracy of the system and calculated
many
of performance metrics which
help
in explaining the best pre-trained networks and the best classifier.