SARS-COV-2 (COVID-19) detection application via machine learning: comparative analysis and performance evaluation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s42600-023-00316-5.pdf
Reference20 articles.
1. Alakus TB, Turkoglu I. Comparison of deep learning approaches to predict COVID-19 infection. Chaos Solit Fractals. 2020;140:110120.
2. Asif S, Wenhui Y, Jin H, Jinha S. Classification of COVID-19 from chest X-ray images using deep convolutional neural network. In: 2020 IEEE 6th international conference on computer and communications (ICCC). Chengdu, China; 2020. p. 426–33. IEEE.
3. Asif S, Zhao M, Tang F, Zhu Y. A deep learning-based framework for detecting COVID-19 patients using chest X-rays. Multimedia Syst. 2022;28(4):1495–513.
4. Altay O, Ulas M. Prediction of the autism spectrum disorder diagnosis with linear discriminant analysis classifier and K-nearest neighbor in children. In: 2018 6th International Symposium on Digital Forensic and Security (ISDFS). Antalya, Turkey; 2018. p. 1–4. IEEE.
5. Bullock J, Luccioni A, Pham KH, Lam CSN, Luengo-Oroz M. Mapping the landscape of artificial intelligence applications against COVID-19. J Artif Intell Res. 2020;69. AI Access Foundation.
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