Publication: Chest x-ray image classification for viral pneumonia and Сovid-19 using neural networks
Дата
2021
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© 2021, Institution of Russian Academy of Sciences. All rights reserved.The use of neural networks to detect differences in radiographic images of patients with pneumonia and COVID-19 is demonstrated. For the optimal selection of resize and neural network architecture parameters, hyperparameters, and adaptive image brightness adjustment, precision, re-call, and f1-score metrics are used. The high values of these metrics of classification quality (> 0.91) strongly indicate a reliable difference between radiographic images of patients with pneumonia and patients with COVID-19, which opens up the possibility of creating a model with good predictive ability without involving ready-to-use complex models and without pre-training on third-party data, which is promising for the development of sensitive and reliable COVID-19 ex-press-diagnostic methods.
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Chest x-ray image classification for viral pneumonia and Сovid-19 using neural networks / Efremtsev, V.G. [et al.] // Computer Optics. - 2021. - 45. - № 1. - P. 149-153. - 10.18287/2412-6179-CO-765
URI
https://www.doi.org/10.18287/2412-6179-CO-765
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https://www.scopus.com/record/display.uri?eid=2-s2.0-85102474957&origin=resultslist
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000624634200017
https://openrepository.mephi.ru/handle/123456789/23779