Diagnosis of COVID-19 is necessary to prevent and control the disease. Deep learning methods have been considered a fast and accurate method. In this paper, by the parallel combination of three well-known pre-trained networks, we attempted to distinguish coronavirus-infected samples from healthy samples. The negative log-likelihood loss function has been used for model training. CT scan images in the SARS-CoV-2 dataset were used for diagnosis. The SARS-CoV-2 dataset contains 2482 images of lung CT scans, of which 1252 images belong to COVID-19-infected samples. The proposed model was close to 97% accurate.
@article{arxiv.2208.07829,
title = {Diagnosis of COVID-19 disease using CT scan images and pre-trained models},
author = {Faezeh Amouzegar and Hamid Mirvaziri and Mostafa Ghazizadeh-Ahsaee and Mahdi Shariatzadeh},
journal= {arXiv preprint arXiv:2208.07829},
year = {2022}
}