publication . Article . Other literature type . 2020

A comprehensive study on classification of COVID-19 on computed tomography with pretrained convolutional neural networks

Pham, Tuan D.;
Open Access English
  • Published: 09 Oct 2020 Journal: Scientific Reports, volume 10 (eissn: 2045-2322, Copyright policy)
  • Publisher: Nature Publishing Group UK
Abstract
<jats:title>Abstract</jats:title> <jats:p>The use of imaging data has been reported to be useful for rapid diagnosis of COVID-19. Although computed tomography (CT) scans show a variety of signs caused by the viral infection, given a large amount of images, these visual features are difficult and can take a long time to be recognized by radiologists. Artificial intelligence methods for automated classification of COVID-19 on CT scans have been found to be very promising. However, current investigation of pretrained convolutional neural networks (CNNs) for COVID-19 diagnosis using CT data is limited. This study presents an investigation on 16 pretrained CNNs for c...
Subjects
free text keywords: Article, Viral infection, Computer science, Multidisciplinary, COVID-19 ; Viral infection ; Computer science, lcsh:Medicine, lcsh:R, lcsh:Science, lcsh:Q, Computed tomography, medicine.diagnostic_test, medicine, Computer science, Data management, business.industry, business, Image processing, Transfer of learning, Pattern recognition, Coronavirus disease 2019 (COVID-19), Artificial neural network, Convolutional neural network, Artificial intelligence, Tomography
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