Accurate prognosis of Covid-19 using CT scan images with deep learning model and machine learning classifiers
Online Publishing @ NISCAIR
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Title Statement |
Accurate prognosis of Covid-19 using CT scan images with deep learning model and machine learning classifiers |
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Added Entry - Uncontrolled Name |
Gupta, Siddharth ; Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun 248 001, India |
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Uncontrolled Index Term |
Machine Learning, Deep Learning, Coronavirus, Logistic regression (LR), Convolution neural network (CNN) |
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Summary, etc. |
The Covid-19 disease is caused by coronavirus or SARS-CoV-2 has wrecked havoc globally. This epidemic severely impacted the economy of most of the countries across the world and has taken away many lives. To control the pandemic situation many researchers, organizations, and institutes have come up with the pathogenesis and developing vaccines to decimate this disease. Out of the several techniques, one of the techniques use image patterns on Computed Tomography (CT) to detect whether a patient is Covid-19 positive or not. In this work, the SARS-COV-2 dataset has been used for the detection of Covid-19 images and normal images. These dataset images have been fed to various deep learning models for extracting the features and finally passed to various ML classifiers which classify the images as Covid-19 or normal images. The results have established that the VGG19 model along with Logistic Regression (LR) classifier gives the maximum AUC and accuracy of 98.5% and 94.6%. |
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Publication, Distribution, Etc. |
Indian Journal of Radio & Space Physics (IJRSP) 2022-04-27 12:53:20 |
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Electronic Location and Access |
application/pdf http://op.niscair.res.in/index.php/IJRSP/article/view/62085 |
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Data Source Entry |
Indian Journal of Radio & Space Physics (IJRSP); ##issue.vol## 50, ##issue.no## 1 (2021): IJRSP MARCH-2021 |
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Language Note |
en |
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Terms Governing Use and Reproduction Note |
Except where otherwise noted, the Articles on this site are licensed underCreative Commons License: CC Attribution-Noncommercial-No Derivative Works 2.5 India© 2012. The Council of Scientific & Industrial Research, New Delhi. |
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