Sensecor: A framework for COVID-19 variants severity classification and symptoms detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Control and Optimization,Computer Science Applications,Modeling and Simulation,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12530-023-09558-1.pdf
Reference54 articles.
1. Alshazly H, Linse C, Barth E et al (2021) Explainable covid-19 detection using chest ct scans and deep learning. Sensors 21(2):455
2. Bechmann N, Barthel A, Schedl A et al (2022) Sexual dimorphism in covid-19: potential clinical and public health implications. Lancet Diabetes Endocrinol 10(3):221–230
3. Benito-León J, Del Castillo MD, Estirado A et al (2021) Using unsupervised machine learning to identify age-and sex-independent severity subgroups among patients with covid-19: Observational longitudinal study. J Med Internet Res 23(5):e25988
4. Bhat M, Qadri M, Kundroo M et al (2020) Sentiment analysis of social media response on the covid19 outbreak. Brain Behav Immun 87:136
5. Bhatia S, Makhija Y, Jayaswal S et al (2022) Severity and mortality prediction models to triage indian covid-19 patients. PLOS Digital Health 1(3):e0000020
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