Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)

A fusing Transformer and CNN on Interpretable COVID-19 Detection

Authors
Zhuohui Pan1, Yujuan Chen2, *
1School of Zhejiang, University of Finance and Economics, Ulan Bator, China
2School of Zhejiang, University of Finance and Economics, Ulan Bator, China
*Corresponding author. Email: chenyj@zufe.edu.cn
Corresponding Author
Yujuan Chen
Available Online 28 September 2023.
DOI
10.2991/978-94-6463-264-4_46How to use a DOI?
Keywords
COVID-19; CNN; Transformer; Lung segmentation; Transfer Learning
Abstract

Although computer-aided diagnosis has become an important tool for rapid detection of lung diseases, the reliability of algorithm visualization on chest X-ray (CXR) images remains a challenge. This study explores the detection performance of a fusion model combining Transformer and CNN models. A decision constraint module was designed to achieve interpretable pneumonia detection. The performance of the decision constraint module was observed using Grad-CAM technique, and experimental results demonstrate that it outperforms lung mask segmentation. By activating transfer learning, our parallel combination model effectively identifies COVID-19 categories with a test set accuracy of 98.65%.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
28 September 2023
ISBN
10.2991/978-94-6463-264-4_46
ISSN
2589-4900
DOI
10.2991/978-94-6463-264-4_46How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Zhuohui Pan
AU  - Yujuan Chen
PY  - 2023
DA  - 2023/09/28
TI  - A fusing Transformer and CNN on Interpretable COVID-19 Detection
BT  - Proceedings of the 2023 3rd International Conference on Education, Information Management and Service Science (EIMSS 2023)
PB  - Atlantis Press
SP  - 410
EP  - 419
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-264-4_46
DO  - 10.2991/978-94-6463-264-4_46
ID  - Pan2023
ER  -