COVID-19 CT-images diagnosis and severity assessment using machine learning algorithm
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
https://link.springer.com/content/pdf/10.1007/s10586-023-03972-5.pdf
Reference37 articles.
1. Alyasseri, Z.A.A.: Review on COVID-19 diagnosis models based on machine learning and deep learning approaches. Expert. Syst. 39(3), e12759 (2022)
2. Alzubaidi, M.A., et al.: A novel computational method for assigning weights of importance to symptoms of COVID-19 patients. Artif. Intell. Med. 112, 102018 (2021)
3. Amini, N., Shalbaf, A.: Automatic classification of severity of COVID-19 patients using texture feature and random forest based on computed tomography images. Int. J. Imaging Syst. Technol. 32(1), 102–110 (2022)
4. Aswathy, A.L., Hareendran, A., Vinod Chandra, S.S.: COVID-19 diagnosis and severity detection from CT-images using transfer learning and back propagation neural network. J. Infect. Public Health 14(10), 1435–1445 (2021)
5. Al-Azawi, R.J., et al.: Efficient classification of COVID-19 CT scans by using q-transform model for feature extraction. PeerJ Comput. Sci. 7, e553 (2021)
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