Covid-19 Analysis using Deep Learning Methods and Computed Tomography Scans
3rd IEEE Bombay Section Signature Conference, IBSSC 2021
; 2021.
Article
in English
| Scopus | ID: covidwho-1714000
ABSTRACT
Covid-19 has quickly emerged as a global threat, tipping the world into a new phase. The delay in medical care because of the quickly rising Covid-19 cases makes it necessary to overcome the manual and time taking technique such as RTPCR. This paper implements different pre-trained CNN feature extraction models using various Machine Learning (ML) classifiers on chest CT scans to analyze Covid-19 infected patients. It may be observed from the obtained results that accuracy of 96.4% was obtained using the VGG16 model and neural network classifier. The implementation of pre-trained models and classifiers reduce the time taken for manual detection of disease and helps doctors to prevent life of a patient. © 2021 IEEE.
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
3rd IEEE Bombay Section Signature Conference, IBSSC 2021
Year:
2021
Document Type:
Article
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