Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.
- DOI
- 10.2196/78471
- Published
- 2026 Jun 4
- Container
- JMIR medical informatics
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.2196/78471,
title = {Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.},
author = {Savvopoulos S and Papadopoulou A and Karavalakis G and Sakellari I and Georgolopoulos G and Argyropoulos C and Yannaki E and Hatzikirou H},
year = {2026},
journal = {JMIR medical informatics},
doi = {10.2196/78471},
url = {https://doi.org/10.2196/78471}
}RIS
TY - JOUR TI - Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial. AU - Savvopoulos S AU - Papadopoulou A AU - Karavalakis G AU - Sakellari I AU - Georgolopoulos G AU - Argyropoulos C AU - Yannaki E AU - Hatzikirou H PY - 2026 JO - JMIR medical informatics DO - 10.2196/78471 UR - https://doi.org/10.2196/78471 ER -
APA
S, S., A, P., G, K., I, S., G, G., C, A., E, Y., & H, H. (2026). Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.. JMIR medical informatics. https://doi.org/10.2196/78471
Source records
- pubmed · retrieved 2026-09-25T00:26:39.529Z