Deep learning driven framework for COVID-19 detection – A Mobile/Web application
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Full Text |
Pdf
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Author |
Syeda Dua Fatima, Muhammad Waleed Khan, Kashif Sultan and Natasha Shahid
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e-ISSN |
1819-6608 |
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On Pages
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121-126
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Volume No. |
18
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Issue No. |
02
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Issue Date |
March 03, 2023
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DOI |
https://doi.org/10.59018/012328
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Keywords |
COVID-19, CNN, VGG1.
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Abstract
Due to the rapid spread of COVID-19, this disease has become a global threat to public health. COVID-19 detection via radiographic images such as CXR and HRCT is one of the most effective techniques. Using deep Learning models, the current study investigates COVID-19 disease on radiographic images. This project proposes a deep learning model for HRCT and CXR images to predict a patient's condition. The proposed model classifies images by incorporating VGG16 deep learning models. In addition, symptom analysis is performed to forecast COVID-19. For symptom analysis, the xgboost algorithm is used. Lastly, a mobile/web application for detecting COVID-19 using deep learning models on radiographic images is developed. This work may serve as a resource for other researchers seeking to advance the development of deep learning applications for medical imaging.
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