TY - JOUR
T1 - Covid-19 classification using X-Ray imaging with ensemble learning
AU - Siswantining, T.
AU - Parlindungan, R.
N1 - Funding Information:
This study is supported by PUTI Proceedings Research Grant from University of Indonesia: NKB-962/UN.2RST/HKP.05.00/2020. The authors are thankful to all parties that involve in the process of writing this paper.
Publisher Copyright:
© 2021 Institute of Physics Publishing. All rights reserved.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1/7
Y1 - 2021/1/7
N2 - Coronavirus (Covid-19) first appeared in Wuhan, December 2019, and continues to spread rapidly to other countries.one of the countries infected with the Covid-19 virus is Indonesia. In Indonesia, the spread of this virus is very fast. Therefore, we need a detection system to detect people who are infected with this virus or not. Rapid detection of Covid-19 can contribute to control the spread of this disease. Chest x-ray images are one of the first imaging techniques to play an important role in the diagnosis of Covid-19. This research data uses chest x-ray images dataset in the Covid-19 cases. The data used in this study were 170 images data with 130 data for training data and 40 for testing data. In this study, the Neural Network, Support Vector Machine (SVM), and Convolutional Neural Network (CNN) methods were used, then applied to Stacking which is one of the methods of Ensemble Learning. The results of this study indicate that the best accuracy is obtained from the Stacking model with an accuracy of 95%.
AB - Coronavirus (Covid-19) first appeared in Wuhan, December 2019, and continues to spread rapidly to other countries.one of the countries infected with the Covid-19 virus is Indonesia. In Indonesia, the spread of this virus is very fast. Therefore, we need a detection system to detect people who are infected with this virus or not. Rapid detection of Covid-19 can contribute to control the spread of this disease. Chest x-ray images are one of the first imaging techniques to play an important role in the diagnosis of Covid-19. This research data uses chest x-ray images dataset in the Covid-19 cases. The data used in this study were 170 images data with 130 data for training data and 40 for testing data. In this study, the Neural Network, Support Vector Machine (SVM), and Convolutional Neural Network (CNN) methods were used, then applied to Stacking which is one of the methods of Ensemble Learning. The results of this study indicate that the best accuracy is obtained from the Stacking model with an accuracy of 95%.
UR - http://www.scopus.com/inward/record.url?scp=85100752715&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1722/1/012072
DO - 10.1088/1742-6596/1722/1/012072
M3 - Conference article
AN - SCOPUS:85100752715
SN - 1742-6588
VL - 1722
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012072
T2 - 10th International Conference and Workshop on High Dimensional Data Analysis, ICW-HDDA 2020
Y2 - 12 October 2020 through 15 October 2020
ER -