Public Article
-
verified
COVID-19 OUTBREAK ANALYSIS USING CONVOLUTIONAL NEURAL NETWORKS ON X-RAY IMAGES
ISSN: 2582 - 9130Publisher: author   
COVID-19 OUTBREAK ANALYSIS USING CONVOLUTIONAL NEURAL NETWORKS ON X-RAY IMAGES
Indexed in
Technology and Engineering
ARTICLE-FACTOR
1.3
Article Basics Score: 2
Article Transparency Score: 3
Article Operation Score: 2
Article Articles Score: 2
Article Accessibility Score: 2
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-1802
Publisher: Krishma Publication
International Journal Address (IAA):
IAA.ZONE/2582384059130
eISSN
:
2582 - 9130
VALID
ISSN Validator
Abstract
Covid-19 expanding to coronavirus disease 19 is a serious threat to humanity and millions have perished because of it. Earlier vaccine development was a very tough task, so people relied on herd immunity and plasma therapy to battle this disease. But now, Covid-19 vaccine is complete and there are many vaccines around different countries. It is still not enough to control the spread of the disease, since vaccination of the whole inhabitants will take a significant amount of time. In this tough Covid-19 times, we decided to build something related to it. Any technological tool enabling rapid screening of the COVID-19 infection with high accuracy can be crucially helpful to the healthcare professionals. The main clinical tool currently in use for the diagnosis of COVID-19 is the Reverse transcription polymerase chain reaction (RT-PCR), which is expensive, less-sensitive and requires specialized medical personnel. X-ray imaging is an eas...