TY - GEN
T1 - Deep learning with concatenate model to detect COVID-19 lung disease with CT scan images
AU - Rahman, Alrafiful
AU - Bustamam, Alhadi
N1 - Publisher Copyright:
© 2022 Author(s).
PY - 2022/3/24
Y1 - 2022/3/24
N2 - The current dangerous viral disease is COVID-19. This viral disease can spread quickly and not only to humans, but animals can also contract the COVID-19 virus disease. Until now, the spread of the COVID-19 virus has not been able to stop. The COVID-19 virus disease is mostly caused by lung infections. To diagnose COVID-19 virus disease with more effective imaging using CT scan images. DenseNet121, MobileNet, Xception, InceptionV3, ResNet50V2, and VGG19 models to check their accuracy in image recognition. To analyze the model performance, 1361 samples from CT scans were collected from the Kaggle warehouse. The DenseNet121-MobileNet model has a sensitivity of 99.76%, a specificity of 99.63%, and an accuracy of 99.76% with a computation time faster. This work focuses only on the methods used to detect patients with COVID-19 in the lungs but does not mention any medical accuracy.
AB - The current dangerous viral disease is COVID-19. This viral disease can spread quickly and not only to humans, but animals can also contract the COVID-19 virus disease. Until now, the spread of the COVID-19 virus has not been able to stop. The COVID-19 virus disease is mostly caused by lung infections. To diagnose COVID-19 virus disease with more effective imaging using CT scan images. DenseNet121, MobileNet, Xception, InceptionV3, ResNet50V2, and VGG19 models to check their accuracy in image recognition. To analyze the model performance, 1361 samples from CT scans were collected from the Kaggle warehouse. The DenseNet121-MobileNet model has a sensitivity of 99.76%, a specificity of 99.63%, and an accuracy of 99.76% with a computation time faster. This work focuses only on the methods used to detect patients with COVID-19 in the lungs but does not mention any medical accuracy.
UR - http://www.scopus.com/inward/record.url?scp=85127936558&partnerID=8YFLogxK
U2 - 10.1063/5.0072411
DO - 10.1063/5.0072411
M3 - Conference contribution
AN - SCOPUS:85127936558
T3 - AIP Conference Proceedings
BT - International Conference on Science and Applied Science, ICSAS 2021
A2 - Purnama, Budi
A2 - Nugraha, Dewanta Arya
A2 - Suparmi, A.
PB - American Institute of Physics Inc.
T2 - 2021 International Conference on Science and Applied Science, ICSAS 2021
Y2 - 6 April 2021 through 6 April 2021
ER -