A Deep Learning Approach for COVID-19 8 Viral Pneumonia Screening with X-ray Images
| Autor: | Faizan Ahmed, Fazel Keshtkar, Syed Ahmad Chan Bukhari |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Public Administration
Coronavirus disease 2019 (COVID-19) Computer Networks and Communications Computer science Machine learning computer.software_genre Convolutional neural network 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Medical imaging Screening method medicine 030304 developmental biology 0303 health sciences business.industry Deep learning medicine.disease Computer Science Applications Viral pneumonia X ray image Artificial intelligence business computer Software Information Systems Healthcare system |
| Zdroj: | Digital Government: Research and Practice. 2:1-12 |
| ISSN: | 2639-0175 2691-199X |
| DOI: | 10.1145/3431804 |
| Popis: | Beginning in December 2019, the spread of the novel Coronavirus (COVID-19) has exposed weaknesses in healthcare systems across the world. To sufficiently contain the virus, countries have had to carry out a set of extraordinary measures, including exhaustive testing and screening for positive cases of the disease. It is crucial to detect and isolate those who are infected as soon as possible to keep the virus contained. However, in countries and areas where there are limited COVID-19 testing kits, there is an urgent need for alternative diagnostic measures. The standard screening method currently used for detecting COVID-19 cases is RT-PCR testing, which is a very time-consuming, laborious, and complicated manual process. Given that nearly all hospitals have X-ray imaging machines, it is possible to use X-rays to screen for COVID-19 without the dedicated test kits and separate those who are infected and those who are not. In this study, we applied deep convolutional neural networks on chest X-rays to determine this phenomena. The proposed deep learning model produced an average classification accuracy of 90.64% and F1-Score of 89.8% after performing 5-fold cross-validation on a multi-class dataset consisting of COVID-19, Viral Pneumonia, and normal X-ray images. |
| Databáze: | OpenAIRE |
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