Serte S et al (2021) Deep learning for diagnosis of COVID-19 using 3D CT scans. Togacar M et al (2020) COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches. In: Santosh KC, Joshi A (eds) COVID-19: Prediction, Decision-Making, and its Impacts. Cureus 12(7):e9448Ĭhen Y (2020) Covid-19 Classification Based on Gray-Level Co-occurrence Matrix and Support Vector Machine.
J Med Internet Res 22(6):13 ( e19569)Ĭohen JP et al (2020) Predicting COVID-19 pneumonia severity on chest x-ray with deep learning. Ko H et al (2020) COVID-19 pneumonia diagnosis using a simple 2d deep learning framework with a single chest ct image: model development and validation. Ni QQ et al (2020) A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images. Tiwari A et al (2022) Deep learning-based automated multiclass classification of chest X-rays into Covid-19, normal, bacterial pneumonia and viral pneumonia. Liang S et al (2022) FCF: Feature complement fusion network for detecting COVID-19 through CT scan images. Ouafi M et al (2022) Rapid syndromic testing for respiratory viral infections in children attending the emergency department during COVID-19 pandemic in Lille, France, 2021–2022. The developed web app can help the users upload their own images and give the prediction results. Our SCNN model is promising in diagnosing COVID-19. It performs better than ten state-of-the-art COVID-19 diagnosis methods. The SCNN model performs better than the ReLU-based backbone network and LReLU-based backbone network, indicating the effectiveness of the Swish function. A web app is developed based on the proposed SCNN model. Our model is named Swish-based CNN (SCNN).
The multiple-way data augmentation is utilized to enhance the training set. Then, we utilize the Swish activation function to replace traditional ReLU. We first propose a 12-layer CNN-based backbone network. CT-based diagnosis methods need special expert knowledge, and the labeling procedure is tedious. COVID-19 has triggered 6.42 million death tolls, and more than 586 million confirmed positive cases until 10/Aug/2022.
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