A Novel Ensemble-based Classifier for Detecting the COVID-19 Disease for Infected Patients
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s10796-021-10132-w.pdf
Reference61 articles.
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2. Abdel-Basset, M., Chang, V., & Mohamed, R. (2020b). Hsma_woa: A hybrid novel slime mould algorithm with whale optimization algorithm for tackling the image segmentation problem of chest x-ray images. Applied Soft Computing, 95, 106642.
3. Abdel-Basset, M., Chang, V., & Nabeeh, N.A. (2020c). An intelligent framework using disruptive technologies for covid-19 analysis. Technological Forecasting and Social Change, 120431.
4. Abdel-Basset, M., Chang, V., Hawash, H., Chakrabortty, R.K., & Ryan, M. (2021). Fss-2019-ncov: A deep learning architecture for semi-supervised few-shot segmentation of covid-19 infection. Knowledge-Based Systems, 212, 106647.
5. Abdel-Basset, M., Chang, V., & Nabeeh, N.A. (2021). An intelligent framework using disruptive technologies for covid-19 analysis. Technological Forecasting and Social Change, 163, 120431.
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