Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games.
- DOI
- 10.1038/s41598-024-59397-6
- Published
- 2024 Apr 18
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-024-59397-6,
title = {Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games.},
author = {Xiao H and Tian Y and Gao H and Cui X and Dong S and Xue Q and Yao D},
year = {2024},
journal = {Scientific reports},
doi = {10.1038/s41598-024-59397-6},
url = {https://doi.org/10.1038/s41598-024-59397-6}
}RIS
TY - JOUR TI - Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games. AU - Xiao H AU - Tian Y AU - Gao H AU - Cui X AU - Dong S AU - Xue Q AU - Yao D PY - 2024 JO - Scientific reports DO - 10.1038/s41598-024-59397-6 UR - https://doi.org/10.1038/s41598-024-59397-6 ER -
APA
H, X., Y, T., H, G., X, C., S, D., Q, X., & D, Y. (2024). Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games.. Scientific reports. https://doi.org/10.1038/s41598-024-59397-6
Source records
- pubmed · retrieved 2026-09-26T03:23:56.923Z