COVID-19 Detected Automatically From CT Images With Ensemble Learning And A Convolutional Neural Network
R. Anitha, M. Saranya, C. Vijayashanthi
COVID-19; Auto detections; CAT; Machine intelligence techniques
Corona Virus Disease (COVID-19), caused by a novel coronavirus, is a worldwide pandemic that has claimed millions of lives. The disease is still not under control a year after it first appeared. COVID-19 is resurfacing in several countries, posing a major threat. COVID-19 can be contained and diagnosed early, preventing large-scale spread. COVID-19 diagnosis with RT-PCR is the gold standard. . However, in most parts of the world, the ability to perform RT-PCR tests is limited. CT is useful in the detection of COVID-19 studies. As a readily available and less expensive modality, CT could be used as a substitute for RT-PCR tests in areas where RT-PCR testing is not available. Machine intelligence algorithms may extract information from CT images and classify them into COVID-19 and non-COVID categories. The most extensively used machine intelligence technology for disease prediction from photos is the convolutional neural network (CNN). COVID-19 identification using various pre-trained CNNS is compared in this work.
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Unique Paper ID: 155228

Publication Volume & Issue: Volume 9, Issue 1

Page(s): 313 - 318
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