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Erschienen in:
Design and Implementation of an IoT-Based Indoor Hydroponics Farm with Automated Climate and Light Control Kapitel lesen Erstes Kapitel lesen

2023 | OriginalPaper | Buchkapitel

COVID Detection from Chest X-Ray Images Using Deep Learning Model

verfasst von : Parth Nimbadkar, Dhruv Patel, Aayush Panchal, Jai Prakash Verma, Jigna Patel

Erschienen in: Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security

Verlag: Springer Nature Singapore

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Abstract

The current COVID-19 disease outbreak has been quite difficult and challenging for human society. Early diagnosis of the virus in people and quarantining them are now vital due to the virus’ quick spread around the globe. Currently, the most widely used method for testing for COVID-19 is RT-PCR. Though it is widely been used, its accuracy is not as desired. From CXR images, we have proposed using neural networks to forecast a patient’s COVID-19 infection status. The COVIDX CXR dataset has been used to train our model. To use the model with ease for the general public, we have developed a web application using Flask for the backend and HTML, CSS, and JavaScript. Using this web application, the user can get the COVID report in a few seconds.

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Metadaten
Titel
COVID Detection from Chest X-Ray Images Using Deep Learning Model
verfasst von
Parth Nimbadkar
Dhruv Patel
Aayush Panchal
Jai Prakash Verma
Jigna Patel
Copyright-Jahr
2023
Verlag
Springer Nature Singapore
Buch
Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security

Print ISBN: 978-981-9914-78-4

Electronic ISBN: 978-981-9914-79-1

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-981-99-1479-1_33