Page 45 - AIH-2-1
P. 45
Artificial Intelligence in Health Deep learning on chest X-ray and CT for COVID-19
com. Accessed April 9, 2021. https://kaggle.com/ 10. Dosovitskiy A, Beyer L, Kolesnikov A, et al. An image is Worth
paultimothymooney/chest-xray-pneumonia 16x16 Words: Transformers for Image Recognition at Scale;
(5) Gogineni A. AjayKumarGogineni777/covid_cnn. 2020.
GitHub. Published October 16, 2020. Accessed April doi: 10.48550/arXiv.2010.11929
10, 2021. https://github.com/AjayKumarGogineni777/ 11. Radford A, Kim JW, Hallacy C, et al. Learning Transferable
covid_cnn Visual Models From Natural Language Supervision.
References arXiv:210300020; 2021. Available from: https://arxiv.org/
abs/2103.00020 [Last accessed on 2023 Mar 05].
1. World Health Organization. Determinants of Health; 2023. 12. WHO. COVAX: Working for Global Equitable Access to
Available from: https://www.who.int [Last accessed on 2024 COVID-19 Vaccines. World Health Organization; 2020.
Sep 16].
Available from: https://www.who.int/initiatives/act-
2. Pathak AD, Saran D, Mishra S, Hitesh M, Bathula S, accelerator/covax [Last accessed on 2021 Apr 09].
Sahu KK. Smart war on COVID-19 and global pandemics: 13. Cleverley J, Piper J, Jones MM. The role of chest radiography
Integrated AI and blockchain ecosystem. Panigrahi CR, in confirming covid-19 pneumonia. BMJ. 2020;370:m2426.
Pati B, Rath M, Buyya R, editors. Computational Modeling
and Data Analysis in COVID-19 Research. United States: doi: 10.1136/bmj.m2426
CRC Press; 2021.
14. Zu ZY, Jiang MD, Xu PP, et al. Coronavirus disease 2019
doi: 10.1201/9781003137481-5 (COVID-19): A perspective from China. Radiology.
2020;296(2):E15-E25.
3. Kishore R, Jha PK, Das S, Agarwal D, Maloo T, Pegu H,
et al. A Kinetic Model for Qualitative Understanding and doi: 10.1148/radiol.2020200490
Analysis of the Effect of Complete Lockdown Imposed by 15. Wang L, Lin ZQ, Wong A. COVID-Net: A tailored
India for Controlling the COVID-19 disease spread by the deep convolutional neural network design for detection
SARS-CoV-2 virus.
of COVID-19 cases from chest X-ray images. Sci
doi: 10.48550/arXiv.2004.05684 Rep. 2020;10(1):19549.
4. Varadi M, Anyango S, Deshpande M, et al. AlphaFold protein doi: 10.1038/s41598-020-76550-z
structure database: massively expanding the structural 16. Wang S, Kang B, Ma J, et al. A deep learning algorithm using
coverage of protein-sequence space with high accuracy CT images to screen for Corona virus disease (COVID-19).
models. Nucleic Acids Res. 2021;50(D1):D439-D444.
Eur Radiol. 2021;31:6096-6104.
doi: 10.1093/nar/gkab1061
doi: 10.1007/s00330-021-07715-1
5. Chowdhery A, Narang S, Devlin J, et al. PaLM: Scaling 17. Joaquin AS. Using Deep Learning to Detect NCOV-19 from
Language Modeling with Pathways. arXiv:220402311; 2022. X-Ray Images. Medium; 2020. Available from: https://
Available from: https://arxiv.org/abs/2204.02311 [Last towardsdatascience.com/using-deep-learning-to-detect-
accessed on 2023 Mar 05].
ncov-19-from-x-ray-images-1a89701d1acd [Last accessed
6. Liu Z, Mao H, Wu CY, Feichtenhofer C, Darrell T, Xie S. 2020 Jun 27].
A ConvNet for the 2020s. arXiv:220103545; 2022. Available 18. Ismael AM, Şengür A. Deep learning approaches for
from: https://arxiv.org/abs/2201.03545 [Last accessed on COVID-19 detection based on chest X-ray images. Expert
2023 Mar 05].
Syst Appl. 2021;164:114054.
7. Habib A, Hasan J, Kim J. A Lightweight deep learning-based doi: 10.1016/j.eswa.2020.114054
approach for concrete crack characterization using acoustic
emission signals. IEEE Access. 2021;9:104029-50. 19. Zhang J, Xie Y, Pang G, et al. Viral pneumonia screening
on chest x-rays using confidence-aware anomaly detection.
doi: 10.1109/access.2021.3099124
IEEE Trans Med Imaging. 2021;40(3):879-890.
8. Sohaib M, Hasan MJ, Chen J, Zheng Z. Generalizing doi: 10.1109/tmi.2020.3040950
infrastructure inspection: Step transfer learning aided
extreme learning machine for automated crack detection in 20. Hemdan EE, Shouman MA, Mohamed Esmail Karar.
concrete structures. Meas Sci Technol. 2024l;35:055402. COVIDX-Net: A Framework of Deep Learning Classifiers to
Diagnose COVID-19 in X-Ray Images. arXiv. Ithaca: Cornell
doi: 10.1088/1361-6501/ad296c
University; 2020.
9. Liu Z, Lin Y, Cao Y, et al. Swin Transformer: Hierarchical doi: 10.48550/arxiv.2003.11055
Vision Transformer using Shifted Windows. arXiv:210314030;
2021. Available from: https://arxiv.org/abs/2103.14030 [Last 21. Jain R, Gupta M, Taneja S, Hemanth DJ. Deep learning
accessed on 2023 Mar 05]. based detection and analysis of COVID-19 on chest X-ray
Volume 2 Issue 1 (2025) 39 doi: 10.36922/aih.2888

