At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.
- DOI
- 10.1038/s41598-024-63212-7
- Published
- 2024 Jul 16
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-63212-7,
title = {At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.},
author = {Mesinovic M and Wong XC and Rajahram GS and Citarella BW and Peariasamy KM and van Someren Greve F and Olliaro P and Merson L and Clifton L and Kartsonaki C and ISARIC Characterisation Group},
year = {2024},
journal = {Scientific reports},
doi = {10.1038/s41598-024-63212-7},
url = {https://doi.org/10.1038/s41598-024-63212-7}
}RIS
TY - JOUR TI - At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods. AU - Mesinovic M AU - Wong XC AU - Rajahram GS AU - Citarella BW AU - Peariasamy KM AU - van Someren Greve F AU - Olliaro P AU - Merson L AU - Clifton L AU - Kartsonaki C AU - ISARIC Characterisation Group PY - 2024 JO - Scientific reports DO - 10.1038/s41598-024-63212-7 UR - https://doi.org/10.1038/s41598-024-63212-7 ER -
APA
M, M., XC, W., GS, R., BW, C., KM, P., F, V. S. G., P, O., L, M., L, C., C, K., & Group, I. C. (2024). At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.. Scientific reports. https://doi.org/10.1038/s41598-024-63212-7
Source records
- pubmed · retrieved 2026-09-26T07:20:45.656Z