Covid-19 Prediction Using Deep Convolutional Neural Networks
DOI:
https://doi.org/10.46243/jst.2021.v6.i04.pp345-351Keywords:
Deep Convolutional Learning, VGG16, CNN Model, COVID-19Abstract
The currently available methods such as RT-PCR for the detection of the novel coronavirus disease fail due to restricted supply of test kits and few favourable signs of illness in the early phases, requiring the use of alternative solutions. The use of an Artificial Intelligence (AI) tool, could assist the world in developing an additional disease prevention regulation. An automatic detection technique is provided in this method, which leverages information from Computer Tomography (CT) images to train the deep learning model CNN architecture. CNNs are the best deep learning model option due to its promising accuracy for biomedical images and availability of fewer samples, which satisfies the need for CNN training. The presented paper aims to discuss the various aspects of the system, beginning with a brief summary and gradually progressing to explain the various implementations, which include the datasets used, the use of the State of the Art (SOTA), and a discussion of the various metrics used for evaluation. Finally, a user-interactive system is presented that employs the qualified model in the area.
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