Immune response recognition and classification of lymphopenia in severe coronavirus disease-2019.
In: AIP Conference Proceedings; 11/8/2022, Vol. 2481 Issue 1, p1-7, 7p; Jg. 2481 (2022-11-08) 1, S. 1-7
Konferenz
Zugriff:
The lymphocyte count was used as a marker in COVID-19. To investigate the relationship between lymphocyte count at admission and COVID-19 severity, we conducted a detailed study and meta-analysis using a machine learning (ML) approach-based artificial immune system. We'd also like to see if patient characteristics such as age and health have an impact on the association between lymphocyte count and COVID-19. To provide an approximation, we apply the supervised machine learning technique. We use the supervised machine learning method (Immunos –R) to give an approach to build an artificial immune network to get accurate analyses response in T cells (cd4+cd8) without doing in-vitro laboratory studies. Accuracy rate for lower lymphocyte count(T lymphocytes cells subset using Immunos –R) mean difference is 84 % for lymphopenia. [ABSTRACT FROM AUTHOR]
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Titel: |
Immune response recognition and classification of lymphopenia in severe coronavirus disease-2019.
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Autor/in / Beteiligte Person: | Dhyani, Manita ; Bordoloi, Dibyahash |
Quelle: | AIP Conference Proceedings; 11/8/2022, Vol. 2481 Issue 1, p1-7, 7p; Jg. 2481 (2022-11-08) 1, S. 1-7 |
Veröffentlichung: | 2022 |
Medientyp: | Konferenz |
ISSN: | 0094-243X (print) |
DOI: | 10.1063/5.0110247 |
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