Authors :
Lim Zi Heng; Lim Jia Qi
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
http://tinyurl.com/5n6epd9n
Scribd :
http://tinyurl.com/2xermvd2
DOI :
https://doi.org/10.5281/zenodo.10669604
Abstract :
The onset of the Coronavirus Disease 2019
(COVID-19) outbreak in early December 2019 has had
profound and far-reaching repercussions on global public
health. Despite being the gold standard for diagnosis,
reverse transcription-polymerase chain reaction (RT-
PCR) alone is unable to address the pandemic’s urgent
need for rapid and efficient diagnostic methods because
of its time-consuming and complex nature. In this study,
we propose a novel convolutional neural network (CNN)
model, which is trained with a publicly available dataset,
with targets of the normal, COVID-19, and viral
pneumonia classes. The trained model achieved accuracy
of 97.17% and specific recall of 94% in COVID-19 cases.
A web application developed using the Python Flask
framework is developed, whereby the users are able to
upload X-ray images and acquire the prediction results
and gradient activation map (Grad-CAM) of the images.
This web app can help to provide a second opinion to
medical practitioners regarding COVID-19 diagnosis.
Keywords :
CNN, COVID-19 Diagnosis, GradCAM, Web Application, X-ray İmages.
The onset of the Coronavirus Disease 2019
(COVID-19) outbreak in early December 2019 has had
profound and far-reaching repercussions on global public
health. Despite being the gold standard for diagnosis,
reverse transcription-polymerase chain reaction (RT-
PCR) alone is unable to address the pandemic’s urgent
need for rapid and efficient diagnostic methods because
of its time-consuming and complex nature. In this study,
we propose a novel convolutional neural network (CNN)
model, which is trained with a publicly available dataset,
with targets of the normal, COVID-19, and viral
pneumonia classes. The trained model achieved accuracy
of 97.17% and specific recall of 94% in COVID-19 cases.
A web application developed using the Python Flask
framework is developed, whereby the users are able to
upload X-ray images and acquire the prediction results
and gradient activation map (Grad-CAM) of the images.
This web app can help to provide a second opinion to
medical practitioners regarding COVID-19 diagnosis.
Keywords :
CNN, COVID-19 Diagnosis, GradCAM, Web Application, X-ray İmages.
