Indah  Soesanti, 
    Analysis of Covid-19 Based on Deep Learning,
    Journal of Engineering and Applied Sciences,
    Volume 16,Issue 2,
    2021,
    Pages 94-102,
    ISSN 1816-949x,
    jeasci.2021.94.102,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2021.94.102)
    Abstract: Coronavirus disease 2019 (COVID-19) caused
by severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2) was first identified in December 2019.
The disease can be detected by using Computed
Tomography (CT) medical image analysis. The methods
used for Covid-19 detection are based on Deep Learning.
Deep Learning Model used are 3D ResNet34, VGG,
AlexNet, VGG-16,VGG-19, SquezeeNet, GoogleNet,
MobileNet-V2, ResNet-18, ResNet-50, ResNet-101 and
Xception. The researchers use public datasets from patient
data Covid-19 and Non-Covid-19. One of the researchers
applies the methods for cross dataset. The results from the
research show that Deep Learning has high performance
and can solve the problem of Covid-19 image
classification and Covid-19 detection.
    Keywords: Covid-19;analysis;deep learning;CT;ResNet