  This paper presents our solution for the first challenge of the 3rd Covid-19
competition, which is part of the "AI-enabled Medical Image Analysis Workshop"
organized by IEEE International Conference on Acoustic, Speech and Signal
Processing (ICASSP) 2023. Our proposed solution is based on a Resnet as a
backbone network with the addition of attention mechanisms. The Resnet provides
an effective feature extractor for the classification task, while the attention
mechanisms improve the model's ability to focus on important regions of
interest within the images. We conducted extensive experiments on the provided
dataset and achieved promising results. Our proposed approach has the potential
to assist in the accurate diagnosis of Covid-19 from chest computed tomography
images, which can aid in the early detection and management of the disease.
