Enhancing predictive accuracy in smart health systems through hybrid machine learning models and sensitivity analysis
- DOI
- 10.1080/10255842.2025.2584378
- Published
- 2025-11-12
- Container
- Computer Methods in Biomechanics and Biomedical Engineering
- Publisher
- Informa UK Limited
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1080/10255842.2025.2584378,
title = {Enhancing predictive accuracy in smart health systems through hybrid machine learning models and sensitivity analysis},
author = {Gui Wu and Xin Luo and Shi Qian and Zejin Liu and Ye Liu},
year = {2025},
journal = {Computer Methods in Biomechanics and Biomedical Engineering},
doi = {10.1080/10255842.2025.2584378},
url = {https://doi.org/10.1080/10255842.2025.2584378}
}RIS
TY - JOUR TI - Enhancing predictive accuracy in smart health systems through hybrid machine learning models and sensitivity analysis AU - Gui Wu AU - Xin Luo AU - Shi Qian AU - Zejin Liu AU - Ye Liu PY - 2025 JO - Computer Methods in Biomechanics and Biomedical Engineering DO - 10.1080/10255842.2025.2584378 UR - https://doi.org/10.1080/10255842.2025.2584378 ER -
APA
Wu, G., Luo, X., Qian, S., Liu, Z., & Liu, Y. (2025). Enhancing predictive accuracy in smart health systems through hybrid machine learning models and sensitivity analysis. Computer Methods in Biomechanics and Biomedical Engineering. https://doi.org/10.1080/10255842.2025.2584378
Source records
- crossref · retrieved 2026-09-26T12:37:35.941Z