Enhancing predictive accuracy in smart health systems through hybrid machine learning models and sensitivity analysis

Gui Wu, Xin Luo, Shi Qian, Zejin Liu, Ye Liu

Open source

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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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

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