CovidViT: a novel neural network with self-attention mechanism to detect Covid-19 through X-ray images.
Int J Mach Learn Cybern
; : 1-15, 2022 Oct 19.
Article
in English
| MEDLINE | ID: covidwho-2287507
ABSTRACT
Since the emergence of the novel coronavirus in December 2019, it has rapidly swept across the globe, with a huge impact on daily life, public health and the economy around the world. There is an urgent necessary for a rapid and economical detection method for the Covid-19. In this study, we used the transformers-based deep learning method to analyze the chest X-rays of normal, Covid-19 and viral pneumonia patients. Covid-Vision-Transformers (CovidViT) is proposed to detect Covid-19 cases through X-ray images. CovidViT is based on transformers block with the self-attention mechanism. In order to demonstrate its superiority, this research is also compared with other popular deep learning models, and the experimental result shows CovidViT outperforms other deep learning models and achieves 98.0% accuracy on test set, which means that the proposed model is excellent in Covid-19 detection. Besides, an online system for quick Covid-19 diagnosis is built on http//yanghang.site/covid19.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Journal:
Int J Mach Learn Cybern
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS