A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA
Coronavirus is a virus from a large family that can infect humans and animals. Usually, the symptoms associated with a mild infection are similar to the common cold. COVID-19 is a new type of coronavirus that has not been seen in humans before and can infect anyone, because no one’s immune system is...
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| Format: | Article |
| Language: | English |
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AIP Publishing LLC
2025-06-01
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| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0271163 |
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| author | Xiaohua Li Shuai Fu |
| author_facet | Xiaohua Li Shuai Fu |
| author_sort | Xiaohua Li |
| collection | DOAJ |
| description | Coronavirus is a virus from a large family that can infect humans and animals. Usually, the symptoms associated with a mild infection are similar to the common cold. COVID-19 is a new type of coronavirus that has not been seen in humans before and can infect anyone, because no one’s immune system is immune to coronavirus. People suspected of having COVID-19 should be informed immediately if they are actually infected with the virus so that they can isolate themselves, receive appropriate treatment, and inform those who have been in close contact with them. In this study, a new computer-aided method is proposed based on deep learning for the diagnosis of COVID-19 from the x-ray images. The suggested method proposes an optimal Convolutional Neural Network (CNN) to provide a diagnosis system with higher accuracy. The CNN has been optimized by an improved version of the Marine Predator Algorithm. The method is analyzed based on some different measurement indicators, and the results are compared with some state-of-the-art methods. Final simulations showed the higher efficiency of the proposed method toward the others. |
| format | Article |
| id | doaj-art-7bf5aa7c338b42559ed84dfadd54869a |
| institution | Kabale University |
| issn | 2158-3226 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | AIP Advances |
| spelling | doaj-art-7bf5aa7c338b42559ed84dfadd54869a2025-08-20T03:31:06ZengAIP Publishing LLCAIP Advances2158-32262025-06-01156065307065307-1310.1063/5.0271163A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPAXiaohua Li0Shuai Fu1School of Physical Education, Hunan University of Arts and Science, Changde, Hunan 415000, ChinaChangchun Humanities and Sciences College, ChangChun, JiLin 130117, ChinaCoronavirus is a virus from a large family that can infect humans and animals. Usually, the symptoms associated with a mild infection are similar to the common cold. COVID-19 is a new type of coronavirus that has not been seen in humans before and can infect anyone, because no one’s immune system is immune to coronavirus. People suspected of having COVID-19 should be informed immediately if they are actually infected with the virus so that they can isolate themselves, receive appropriate treatment, and inform those who have been in close contact with them. In this study, a new computer-aided method is proposed based on deep learning for the diagnosis of COVID-19 from the x-ray images. The suggested method proposes an optimal Convolutional Neural Network (CNN) to provide a diagnosis system with higher accuracy. The CNN has been optimized by an improved version of the Marine Predator Algorithm. The method is analyzed based on some different measurement indicators, and the results are compared with some state-of-the-art methods. Final simulations showed the higher efficiency of the proposed method toward the others.http://dx.doi.org/10.1063/5.0271163 |
| spellingShingle | Xiaohua Li Shuai Fu A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA AIP Advances |
| title | A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA |
| title_full | A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA |
| title_fullStr | A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA |
| title_full_unstemmed | A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA |
| title_short | A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA |
| title_sort | deep learning approach for accurate covid 19 diagnosis from x ray images using oblmpa |
| url | http://dx.doi.org/10.1063/5.0271163 |
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