Shanmugapriya, I and Sowmya Devi, D (2023) Improving the Response rate of RT PCR testing using deep convolutional encoder. Improving the Response rate of RT PCR testing using deep convolutional encoder. pp. 1-5. ISSN 2665-9174

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Abstract

The sensitivity of the RT-PCR test is limited, and the method itself is laborious and time-consuming to carry out.
When it comes to making a diagnosis of COVID-19, chest CT scans have the potential to be of assistance. If, on the
other hand, the infection does not spread to the lungs, then an abnormality check with a CT scan will not be
necessary. Complementary assays have the potential to considerably reduce the frequency of false-positive results
when they are used in combining with RT-PCR or CT scans. We propose in this study a decision support
system that is based on deep learning and has the capability to evaluate the practically commonly required
laboratory parameters for the purpose of identifying COVID-19. Here dataset contains the 1428 radiographs (224
COVID-19, 504 Healthy, 700 Pneumonia) are considered for experimentation.

Item Type: Article
Additional Information: journal homepage: www.sciencedirect.com/journal/measurement-sensors
Uncontrolled Keywords: RT PCR Response rate Deep convolutional encoder Testing
Divisions: PSG College of Arts and Science > Department of Computer Science
Depositing User: Mr Team Mosys
Date Deposited: 06 Sep 2024 10:19
Last Modified: 06 Sep 2024 10:19
URI: https://ir.psgcas.ac.in/id/eprint/2223

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