DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Science, Engineering and Technology(IJASEAT)-IJASEAT |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-2 ( Apr, 2021 ) | |||||||||
Paper Title |
A Review on Chest X-ray Based Covid 19 Patient Monitoring | |||||||||
Author Name |
Manisha Sahu, Kusum Sharma, Rahul Mishra | |||||||||
Affilition |
Research Scholar, Assistant Professor, Assistant Professor Department of Computer Science and Engineering RSR Rungta College of Engineering and Technology, Bhilai, Chhattisgarh, India | |||||||||
Pages |
1-4 | |||||||||
Abstract |
The year 2019 novel corona virus disease (COVID-19), with a starting point in China, has spread rapidly among people living in other countries, and is approaching approximately 34,986,502 cases worldwide according to the statistics of European Centre for Disease Prevention and Control. There are a limited number of COVID-19 test kits available in hospitals due to the increasing cases daily. Therefore, it is necessary to implement an automatic detection system as a quick alternative diagnosis option to prevent COVID-19 spreading among people. In this study, five pre-trained Convolutional Neural Network (CNN) based models (ResNet50, ResNet101, ResNet152, InceptionV3 and Inception-ResNetV2) have been proposed for the detection of corona virus pneumonia infected patient using chest X-ray radiographs. We have implemented three different binary classifications with four classes (COVID-19, normal (healthy), viral pneumonia and bacterial pneumonia) by using 5-fold cross validation. Keywords - Chest x-ray, Covid 19, monitoring, CNN. | |||||||||
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