COVID-19 Detection Using Chest X-Ray Images Based on Deep Learning
International Journal of Software Science and Computational Intelligence-Ijssci
; 14(1), 2022.
Article
in English
| Web of Science | ID: covidwho-2201332
ABSTRACT
Global public health will be severely impacted by the successive waves of emerging COVID-19 disease. Since 2019 people get sick and die in our daily lives placing a massive burden on our health system. One of the crucial factors that has led to the virus's fast spread is a protracted clinical testing gap before discovering of a positive or negative result. A detection system based on deep learning was developed by using chest X-ray(CXR) images of Covid19 patient and healthy people. In this regard the Convolution Neural Network along with other DNNs have been proved to produce good results. To improve the COVID-19 detection accuracy, we developed model using the deep learning(CNN) approach where we observed an accuracy of 96%. We validated the accuracy by using same dataset through a pretrained VGG16 model and an LSTM model which produced excellent reliable results. Our aim of this research is to implement a reliable Deep Learning model to detect presence of Covid-19 in case of limited availability of chest-Xray images.
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
International Journal of Software Science and Computational Intelligence-Ijssci
Year:
2022
Document Type:
Article
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