WCSE 2022
ISBN: 978-981-18-3959-7 DOI: 10.18178/wcse.2022.06.029

Detecting COVID-19 in Chest X-Ray Images Using Apache Spark and CNN

Yangjun Ou, Yihong Chen, Yuhang Xie, Ziyi Wang

Abstract—COVID-19 is highly contagious and highly pathogenic, It seriously threatens human life and health. Rapid detection of positive COVID-19 cases is very important in stopping the spread of the virus. At early diagnosis, It is the most simple and rapid indicator for judging changes in the illness. As the COVID-19 chest X-ray image dataset continues to expand, Researchers build a CNN-based COVID-19 detection model on Apache Spark. The model can effectively detect positive cases of COVID-19. This article first introduces the big data platform Apache Spark, Deep Learning Technology CNN, transfer learning techniques, etc. Then, it summarizes the characteristics and deficiencies of the research on chest X-ray image recognition of COVID-19 in recent years.Finally, Under the big data thinking, This paper proposes a technical direction for rapid detection of COVID-19 based on the big data analysis platform Apache Spark and the deep learning algorithm CNN for large-scale COVID-19 chest X-ray image datasets.

Index Terms—Chest X-ray image of COVID-19, Apache spark, CNN

Yangjun Ou
School of Electronic Information Engineering,China West Normal University,CHINA
Yihong Chen
School of Computer Science,China West Normal University, CHINA
Yuhang Xie
School of Electronic Information Engineering,China West Normal University,CHINA
Ziyi Wang
School of Computer Science,China West Normal University, CHINA

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Cite:Yangjun Ou, Yihong Chen, Yuhang Xie, Ziyi Wang, "Detecting COVID-19 in Chest X-Ray Images Using Apache Spark and CNN, " Proceedings of 2022 the 12th International Workshop on Computer Science and Engineering (WCSE 2022), pp. 207-211, June 24-27, 2022.