Abstract:
The Covid-19 pandemic has spread frighteningly and rapidly in all countries of the world, forcing humanity to lead an abnormal life, and the matter has been further complicated by the emergence of new strains of this epidemic, which appear to be more infectious and possibly more dangerous. The lack of full control over this epidemic and its new strains and the challenge of developing fully effective vaccinations endangers human life. Fighting against the epidemic has become important, as all these measures could not be taken in the near future. For this reason, it is important to find out whether a person infected with the virus expressed in thousands of people has Covid-19 or not and to take the necessary measures.
For this purpose, in this study, we propose an artificial intelligence-based method has that will speed up the diagnosis of the pandemic by saving labour and expense. In the study, X-Ray images were processed with the most up-to-date deep image processing techniques, and an objective decision support system was created, independent of the doctors’ expertise. Our proposed system can classify x-ray images as Normal, Covid -19, and Viral Pneumonia using pre-trained deep learning networks (AlexNet, MobileNetV2, GoogleNet, ResNet8, and ResNet50) with transfer learning (TL) and K-fold validation (KFCV). The overall accuracies of the networks (AlexNet, MobileNetV2, GoogleNet, ResNet8, and ResNet50) were 98%, 97. 4%, 97. 4%, 97. 4%, 98. 5% respectively.
Also, for the average performance metrics values (Sensitivity, Specificity, Precision, F1-score, and Negative predictive value(NPV)). The best results were recorded by ResNet 50+TL+KFCV (97. 9% Sensitivity, 98. 9% Specificity, 97. 9% Precision, 97. 9 % F1-Score, and 98. 9% NPV ).
It is easy to diagnose in the advanced stages of the disease. As with most diseases, early diagnosis is important in COVID-19. With the proposed system based on deep learning, a very useful tool in combating the pandemic has been created by determining the disease at an early stage. The proposed system can also be used in areas with a shortage of health personnel such as rural and remote areas.
Abstract:
The Covid-19 pandemic has spread
frighteningly
and
rapidly
in all countries of the world, forcing humanity to lead an abnormal life, and the matter has been
further
complicated by the emergence of new strains of this epidemic, which appear to be more infectious and
possibly
more
dangerous
. The lack of full control over this epidemic and its new strains and the challenge of developing
fully
effective vaccinations endangers human life. Fighting against the epidemic has become
important
, as all these measures could not
be taken
in the near future.
For this reason
, it is
important
to find out whether a person infected with the virus expressed in thousands of
people
has Covid-19 or not and to take the necessary measures.
For this purpose, in this study, we propose an artificial intelligence-based method has that will
speed up
the diagnosis of the pandemic by saving
labour
and expense. In the study, X-Ray images
were processed
with the most up-to-date deep image processing techniques, and an objective decision support
system
was created
, independent of the doctors’ expertise. Our proposed
system
can classify x-ray images as Normal,
Covid
-19, and Viral Pneumonia using pre-trained deep learning networks (
AlexNet
, MobileNetV2,
GoogleNet
, ResNet8, and ResNet50) with transfer learning (TL) and K-fold validation (
KFCV
). The
overall
accuracies of the networks (
AlexNet
, MobileNetV2,
GoogleNet
, ResNet8, and ResNet50) were 98%, 97. 4%, 97. 4%, 97.
4%
, 98. 5%
respectively
.
Also
, for the average performance metrics values (Sensitivity, Specificity, Precision, F1-score, and
Negative
predictive value(NPV)). The best results
were recorded
by
ResNet
50+TL+
KFCV
(97. 9% Sensitivity, 98. 9% Specificity, 97.
9%
Precision, 97. 9 % F1-Score, and 98. 9% NPV
)
.
It is easy to diagnose in the advanced stages of the disease. As with most diseases, early diagnosis is
important
in COVID-19. With the proposed
system
based on deep learning, a
very
useful tool in combating the pandemic has
been created
by determining the disease at an early stage. The proposed
system
can
also
be
used
in areas with a shortage of health personnel such as rural and remote areas.